Job description Job Title: Tech Lead (AI/ML) – Machine Learning & Generative AI Location: Nagpur (Hybrid / On-site) Experience: 8–15 years Employment Type: Full-time Job Summary: We are seeking a highly experienced Python Developer with a strong background in traditional Machine Learning and growing proficiency in Generative AI to join our AI Engineering team. This role is ideal for professionals who have delivered scalable ML solutions and are now expanding into LLM-based architectures, prompt engineering, and GenAI productization. You’ll be working at the forefront of applied AI, driving both model performance and business impact across diverse use cases. Key Responsibilities: Design and develop ML-powered solutions for use cases in classification, regression, recommendation, and NLP. Build and operationalize GenAI solutions, including fine-tuning, prompt design, and RAG implementations using models such as GPT, LLaMA, Claude, or Gemini. Develop and maintain FastAPI-based services that expose AI models through secure, scalable APIs. Lead data modeling, transformation, and end-to-end ML pipelines, from feature engineering to deployment. Integrate with relational (MySQL) and vector databases (e.g., ChromaDB, FAISS, Weaviate) to support semantic search, embedding stores, and LLM contexts. Mentor junior team members and review code, models, and system designs for robustness and maintainability. Collaborate with product, data science, and infrastructure teams to translate business needs into AI capabilities. Optimize model and API performance, ensuring high availability, security, and scalability in production environments. Core Skills & Experience: Strong Python programming skills with 5+ years of applied ML/AI experience. Demonstrated experience building and deploying models using TensorFlow, PyTorch, scikit-learn, or similar libraries. Practical knowledge of LLMs and GenAI frameworks, including Hugging Face, OpenAI, or custom transformer stacks. Proficient in REST API design using FastAPI and securing APIs in production environments. Deep understanding of MySQL (query performance, schema design, transactions). Hands-on with vector databases and embeddings for search, retrieval, and recommendation systems. Strong foundation in software engineering practices: version control (Git), testing, CI/CD. Preferred/Bonus Experience: Deployment of AI solutions on cloud platforms (AWS, GCP, Azure). Familiarity with MLOps tools (MLflow, Airflow, DVC, SageMaker, Vertex AI). Experience with Docker, Kubernetes, and container orchestration. Understanding of prompt engineering, tokenization, LangChain, or multi-agent orchestration frameworks. Exposure to enterprise-grade AI applications in BFSI, healthcare, or regulated industries is a plus. What We Offer: Opportunity to work on a cutting-edge AI stack integrating both classical ML and advanced GenAI. High autonomy and influence in architecting real-world AI solutions. A dynamic and collaborative environment focused on continuous learning and innovation. Show more Show less

Built systems that power B2B SaaS products? Want to scale them for real-world impact? Our client is solving some of the toughest data problems in India powering fintech intelligence, risk engines, and decision-making platforms where structured data is often missing. Their systems are used by leading institutions to make sense of complex, high-velocity datasets in real time. We’re looking for a Senior Data Engineer who has helped scale B2B SaaS platforms, built pipelines from scratch, and wants to take complete ownership of data architecture and infrastructure decisions. What You'll Do: Design, build, and maintain scalable ETL pipelines using Python , PySpark , and Airflow Architect ingestion and transformation workflows using AWS services like S3 , Lambda , Glue , and EMR Handle large volumes of structured and unstructured data with a focus on performance and reliability Lead data warehouse and schema design across Postgres , MongoDB , DynamoDB , and Elasticsearch Collaborate cross-functionally to ensure data infrastructure aligns with product and analytics goals Build systems from the ground up and contribute to key architectural decisions Mentor junior team members and guide implementation best practices You’re a Great Fit If You Have: 3 to 7 years of experience in data engineering , preferably within B2B SaaS/AI environments ( mandatory ) Strong programming skills in Python and experience with PySpark , and Airflow Strong expertise in designing, building and deploying data pipelines in product environments Mandatory experience in NoSQL databases Hands-on with AWS data services and distributed data processing tools like Spark or Dask Understanding of data modeling , performance tuning , and database design Experience working in fast-paced, product-driven teams and have seen the 0 to 1 journey Awareness of async programming and how it applies in real-world risk/fraud use cases Experience mentoring or guiding junior engineers is preferred Role Details: Location: Mumbai (On-site WFO) Experience: 3 to 7 years Budget: 20 to 30 LPA (Max) Notice Period: 30 days or less If you're from a B2B SaaS background and looking to solve meaningful, large-scale data problems we’d love to talk. Apply now or reach out directly to learn more. Show more Show less

About ZenDot ZenDot is a cutting-edge technology company building AI-driven solutions that power the next generation of productivity, intelligence, and automation for businesses. Our focus lies in delivering enterprise-grade tools that combine large language models, real-time data, and deep integrations across knowledge ecosystems. We're building a state-of-the-art internal platform for enterprise semantic search, secure document retrieval, and intelligent knowledge graphs . To lead this mission, we are hiring a Senior AI Engineer to architect and implement a search and knowledge engine inspired by world-class products like Glean — but tailored to our own innovation roadmap. Key Responsibilities Lead the end-to-end design and implementation of an enterprise semantic search engine with hybrid retrieval capabilities. Build robust, scalable data ingestion pipelines to index content from sources like Google Workspace, Slack, Jira, Confluence, GitHub, Notion, and more. Design and optimize a reranking and LLM augmentation layer to improve the quality and relevance of search results. Construct an internal knowledge graph mapping users, documents, metadata, and relationships to personalize responses. Implement permission-aware access filters , ensuring secure and role-based query results across users and teams. Collaborate on a modular AI orchestration layer , integrating search, chat, summarization, and task triggers. Maintain model benchmarks, A/B testing frameworks, and feedback loops for continuous learning and improvement. Work closely with product, security, infra, and frontend teams to deliver high-performance and compliant AI solutions . Require Skills & Experience 3+ years of experience in AI/ML engineering with deep expertise in information retrieval (IR) , NLP , and vector search . Strong understanding and hands-on work with BM25, vector stores (Faiss, Weaviate, Vespa, Elasticsearch) . Proficiency in transformer-based models (BERT, RoBERTa, OpenAI embeddings) and document embedding techniques . Experience in building hybrid search pipelines (sparse + dense), rerankers, and multi-modal retrieval systems. Skilled in Python , PyTorch/TensorFlow , and data engineering frameworks (Airflow, Spark, etc.). Familiar with RBAC systems, OAuth2 , and enterprise permissioning logic. Hands-on with graph data structures or knowledge graph tools like Neo4j, RDF, or custom DAG engines. Cloud-native architecture experience (AWS/GCP), Kubernetes, and microservices best practices. Bonus Points For Building or contributing to open-source IR/NLP/search frameworks (e.g., Haystack, Milvus, LangChain). Past work with LLM-driven RAG (Retrieval-Augmented Generation) systems. Familiarity with document-level compliance, access auditing, and SAML/SCIM integrations. Ability to work in fast-paced, zero-to-one product environments with deep ownership. Show more Show less

Role: Snowflake Data Engineer Location: Delhi NCR/Bangalore Year of experience: 4 to 5 Years (Don't apply who less than 4 years) Full Time position Qualifications Experience with Snowflake, DBT (Data Build Tool), and Airflow Location- Delhi/NCR and Bangalore Strong DE with good analytical skills. Skills - hands on DBT, Snowflake and good to have Airflow skills. Good understanding of data architecture- star schema, snowflake schema, fact, and dimensions, data warehousing basics, data models etc. Show more Show less

The purpose of this role is to understand, model and facilitate change in a significant area of the business and technology portfolio either by line of business, geography or specific architecture domain whilst building the overall Architecture capability and knowledge base of the company. Job Description: Role Overview : We are seeking a highly skilled and motivated Cloud Data Engineering Manager to join our team. The role is critical to the development of a cutting-edge reporting platform designed to measure and optimize online marketing campaigns. The GCP Data Engineering Manager will design, implement, and maintain scalable, reliable, and efficient data solutions on Google Cloud Platform (GCP). The role focuses on enabling data-driven decision-making by developing ETL/ELT pipelines, managing large-scale datasets, and optimizing data workflows. The ideal candidate is a proactive problem-solver with strong technical expertise in GCP, a passion for data engineering, and a commitment to delivering high-quality solutions aligned with business needs. Key Responsibilities : Data Engineering & Development : Design, build, and maintain scalable ETL/ELT pipelines for ingesting, processing, and transforming structured and unstructured data. Implement enterprise-level data solutions using GCP services such as BigQuery, Dataform, Cloud Storage, Dataflow, Cloud Functions, Cloud Pub/Sub, and Cloud Composer. Develop and optimize data architectures that support real-time and batch data processing. Build, optimize, and maintain CI/CD pipelines using tools like Jenkins, GitLab, or Google Cloud Build. Automate testing, integration, and deployment processes to ensure fast and reliable software delivery. Cloud Infrastructure Management : Manage and deploy GCP infrastructure components to enable seamless data workflows. Ensure data solutions are robust, scalable, and cost-effective, leveraging GCP best practices. Infrastructure Automation and Management: Design, deploy, and maintain scalable and secure infrastructure on GCP. Implement Infrastructure as Code (IaC) using tools like Terraform. Manage Kubernetes clusters (GKE) for containerized workloads. Collaboration and Stakeholder Engagement : Work closely with cross-functional teams, including data analysts, data scientists, DevOps, and business stakeholders, to deliver data projects aligned with business goals. Translate business requirements into scalable, technical solutions while collaborating with team members to ensure successful implementation. Quality Assurance & Optimization : Implement best practices for data governance, security, and privacy, ensuring compliance with organizational policies and regulations. Conduct thorough quality assurance, including testing and validation, to ensure the accuracy and reliability of data pipelines. Monitor and optimize pipeline performance to meet SLAs and minimize operational costs. Qualifications and Certifications : Education: Bachelor’s or master’s degree in computer science, Information Technology, Engineering, or a related field. Experience: Minimum of 7 to 9 years of experience in data engineering, with at least 4 years working on GCP cloud platforms. Proven experience designing and implementing data workflows using GCP services like BigQuery, Dataform Cloud Dataflow, Cloud Pub/Sub, and Cloud Composer. Certifications: Google Cloud Professional Data Engineer certification preferred. Key Skills : Mandatory Skills: Advanced proficiency in Python for data pipelines and automation. Strong SQL skills for querying, transforming, and analyzing large datasets. Strong hands-on experience with GCP services, including Cloud Storage, Dataflow, Cloud Pub/Sub, Cloud SQL, BigQuery, Dataform, Compute Engine and Kubernetes Engine (GKE). Hands-on experience with CI/CD tools such as Jenkins, GitHub or Bitbucket. Proficiency in Docker, Kubernetes, Terraform or Ansible for containerization, orchestration, and infrastructure as code (IaC) Familiarity with workflow orchestration tools like Apache Airflow or Cloud Composer Strong understanding of Agile/Scrum methodologies Nice-to-Have Skills: Experience with other cloud platforms like AWS or Azure. Knowledge of data visualization tools (e.g., Power BI, Looker, Tableau). Understanding of machine learning workflows and their integration with data pipelines. Soft Skills : Strong problem-solving and critical-thinking abilities. Excellent communication skills to collaborate with technical and non-technical stakeholders. Proactive attitude towards innovation and learning. Ability to work independently and as part of a collaborative team. Location: Bengaluru Brand: Merkle Time Type: Full time Contract Type: Permanent Show more Show less

Job Overview: Diacto is looking for a highly capable Data Architect with 5 to 9 years of experience to lead cloud data platform initiatives with a primary focus on Snowflake and Azure Data Hub. This individual will play a key role in defining the data architecture strategy, implementing robust data pipelines, and enabling enterprise-grade analytics solutions. This is an on-site role based in our Baner, Pune office. Qualifications: B.E./B.Tech in Computer Science, IT, or related discipline MCS/MCA or equivalent preferred Key Responsibilities: Design and implement enterprise-level data architecture with a strong focus on Snowflake and Azure Data Hub Define standards and best practices for data ingestion, transformation, and storage Collaborate with cross-functional teams to develop scalable, secure, and high-performance data pipelines Lead Snowflake environment setup, configuration, performance tuning, and optimization Integrate Azure Data Services with Snowflake to support diverse business use cases Implement governance, metadata management, and security policies Mentor junior developers and data engineers on cloud data technologies and best practices Experience and Skills Required: 5 to 9 years of overall experience in data architecture or data engineering roles Strong, hands-on expertise in Snowflake , including design, development, and performance tuning Solid experience with Azure Data Hub and Azure Data Services (Data Lake, Synapse, etc.) Understanding of cloud data integration techniques and ELT/ETL frameworks Familiarity with data orchestration tools such as DBT, Airflow , or Azure Data Factory Proven ability to handle structured, semi-structured, and unstructured data Strong analytical, problem-solving, and communication skills Nice to Have: Certifications in Snowflake and/or Microsoft Azure Experience with CI/CD tools like GitHub for code versioning and deployment Familiarity with real-time or near-real-time data ingestion Why Join Diacto Technologies? Work with a cutting-edge tech stack and cloud-native architectures Be part of a data-driven culture with opportunities for continuous learning Collaborate with industry experts and build transformative data solutions Competitive salary and benefits with a collaborative work environment in Baner, Pune How to Apply: Option 1 (Preferred) Copy and paste the following link on your browser and submit your application for automated interview process : - https://app.candidhr.ai/app/candidate/gAAAAABoRrcIhRQqJKDXiCEfrQG8Rtsk46Etg4-K8eiwqJ_GELL6ewSC9vl4BjaTwUAHzXZTE3nOtgaiQLCso_vWzieLkoV9Nw==/ Option 2 1. Please visit our website's career section at https://www.diacto.com/careers/ 2. Scroll down to the " Who are we looking for ?" section 3. Find the listing for " Data Architect (Snowflake) " and 4. Proceed with the virtual interview by clicking on " Apply Now ."

Key Responsibilities: Design and develop a modular, scalable AI platform to serve foundation model and RAG-based applications. Build pipelines for embedding generation , document chunking , and indexing . Develop integrations with vector databases like Pinecone , Weaviate , Chroma , or FAISS . Orchestrate LLM flows using tools like LangChain , LlamaIndex , and OpenAI APIs . Implement RAG architectures to combine generative models with structured and unstructured knowledge sources. Create robust APIs and developer tools for easy adoption of AI models across teams. Build observability and monitoring into AI workflows for performance, cost, and output quality. Collaborate with DevOps, Data Engineering, and Product to align platform capabilities with business use cases. Core Skill Set: Strong experience in Python, with deep familiarity in ML/AI frameworks (PyTorch, Hugging Face, TensorFlow). Experience building LLM applications , particularly using LangChain , LlamaIndex , and OpenAI or Anthropic APIs . Practical understanding of vector search , semantic retrieval , and embedding models . Familiarity with AI platform tools (e.g., MLflow, Kubernetes, Airflow, Prefect, Ray Serve). Hands-on with cloud infrastructure (AWS, GCP, Azure) and containerization (Docker, Kubernetes). Solid grasp of RAG architecture design , prompt engineering , and model evaluation . Understanding of MLOps, CI/CD, and data pipelines in production environments. Preferred Qualifications: Experience designing and scaling internal ML/AI platforms or LLMOps tools. Experience with fine-tuning LLMs or customizing embeddings for domain-specific applications. Contributions to open-source AI platform components. Knowledge of data privacy, governance, and responsible AI practices. What You’ll Get: A high-impact role building the core AI infrastructure of our company. Flexible work environment and competitive compensation. Access to cutting-edge foundation models and tooling. Opportunity to shape the future of applied AI within a fast-moving team. Show more Show less

Job Scope: Responsible for creating, monitoring and maintaining various databases - MySQL, Postgres, Oracle, ClickHouse including NoSQL databases like Cassandra, Mongo DB, Scylla DB etc. Automating routine Database Administration, monitoring and alerting activities using shell scripting, python, Perl etc. Providing DB design solutions, hands-on expert using SQL and other DB related tools. Providing solutions for Database High Availability (HA), Data Security, Governance, compliance measures etc. You’ll be Responsible for? Ensure optimal health, integrity, availability, performance, and security of all databases. Develop and maintain data categorization and security standards. Evaluate and recommend new database technologies and management tools; optimize existing and future technology investments to maximize returns. Provide day-to-day support to internal IT support groups, external partners, and customers as required. Manage outsourced database administration services to perform basic monitoring and administrative-level tasks as directed. Participate in change and problem management activities, root cause analysis, and development of knowledge articles to support the organization’s program. Support application testing and production operations. Serve as database administration. Document, monitor, test, and adjust backup and recovery procedures to ensure important data is available in a disaster scenario. Serve as On-Call database administrator on a rotating basis. Develop, Implement, and Maintain MySQL, PostgreSQL, Mongo, ClickHouse, Cassandra, Scylla DB and Oracle Instances including automated scripts for monitoring and maintenance of individual databases. Diligently teaming with the infrastructure, network, database, application, and business intelligence teams to guarantee high data quality and availability. Collaborating with various teams to install Database software updates, patches, version upgrades when required. Performance tuning of Databases, SQL Query tuning, optimizing database designs. Knowledge of schedulers - Cron, or any other new generation schedulers like Apache Airflow Provide subject matter expertise to internal and external project teams, applications developers, and others as needed. Support application testing and production operations. Responsible for implementation and ongoing administration of Data Pipelines What you’d have? B.E./B.Tech/MCA from a premier institute 5-9 years of experience in managing enterprise databases Knowledge and Skills Expert on any three of the databases (covering minimum 1 from SQL and NoSQL database family each) - Oracle, MySQL, PostgreSQL, ClickHouse DB & NoSQL like Mongo DB, Cassandra, Scylla DB, Redis, Aerospike etc. Installing MySQL, PostgreSQL, ClickHouse DB , Oracle , Cassandra, Scylla DB & Mongo DB. Backup and Recovering Oracle, MySQL, Mongo DB, ClickHouse DB Cassandra, Scylla DB and PostgreSQL databases. User level Access: Risks & Threats. Synchronous and Asynchronous replication, converged systems, partitioning, and storage-as-a-service (cloud technologies) Linux operating systems (RHEL, Ubuntu, CentOS), including shell scripting. Windows Server operating system Industry-leading database monitoring tools and platforms Data integration techniques, platforms, and tools Modern database backup technologies and strategies Why join us? Impactful Work : Play a pivotal role in safeguarding Tanla's assets, data, and reputation in the industry. Tremendous Growth Opportunities : Be part of a rapidly growing company in the telecom and CPaaS space, with opportunities for professional development. Innovative Environment: Work alongside a world-class team in a challenging and fun environment, where innovation is celebrated. Tanla is an equal opportunity employer. We champion diversity and are committed to creating an inclusive environment for all employees. www.tanla.com Show more Show less

Dear Candidate, We are hiring a Data Platform Engineer to build and maintain scalable, secure, and reliable data infrastructure for analytics and real-time processing. Key Responsibilities: Design and manage data pipelines, storage layers, and ingestion frameworks. Build platforms for batch and streaming data processing (Spark, Kafka, Flink). Optimize data systems for scalability, fault tolerance, and performance. Collaborate with data engineers, analysts, and DevOps to enable data access. Enforce data governance, access controls, and compliance standards. Required Skills & Qualifications: Proficiency with distributed data systems (Hadoop, Spark, Kafka, Airflow). Strong SQL and experience with cloud data platforms (Snowflake, BigQuery, Redshift). Knowledge of data warehousing, lakehouse, and ETL/ELT pipelines. Experience with infrastructure as code and automation. Familiarity with data quality, security, and metadata management. Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Srinivasa Reddy Kandi Delivery Manager Integra Technologies

Data Architect is responsible to define and lead the Data Architecture, Data Quality, Data Governance, ingesting, processing, and storing millions of rows of data per day. This hands-on role helps solve real big data problems. You will be working with our product, business, engineering stakeholders, understanding our current eco-systems, and then building consensus to designing solutions, writing codes and automation, defining standards, establishing best practices across the company and building world-class data solutions and applications that power crucial business decisions throughout the organization. We are looking for an open-minded, structured thinker passionate about building systems at scale. Role Design, implement and lead Data Architecture, Data Quality, Data Governance Defining data modeling standards and foundational best practices Develop and evangelize data quality standards and practices Establish data governance processes, procedures, policies, and guidelines to maintain the integrity and security of the data Drive the successful adoption of organizational data utilization and self-serviced data platforms Create and maintain critical data standards and metadata that allows data to be understood and leveraged as a shared asset Develop standards and write template codes for sourcing, collecting, and transforming data for streaming or batch processing data Design data schemes, object models, and flow diagrams to structure, store, process, and integrate data Provide architectural assessments, strategies, and roadmaps for data management Apply hands-on subject matter expertise in the Architecture and administration of Big Data platforms, Data Lake Technologies (AWS S3/Hive), and experience with ML and Data Science platforms Implement and manage industry best practice tools and processes such as Data Lake, Databricks, Delta Lake, S3, Spark ETL, Airflow, Hive Catalog, Redshift, Kafka, Kubernetes, Docker, CI/CD Translate big data and analytics requirements into data models that will operate at a large scale and high performance and guide the data analytics engineers on these data models Define templates and processes for the design and analysis of data models, data flows, and integration Lead and mentor Data Analytics team members in best practices, processes, and technologies in Data platforms Qualifications B.S. or M.S. in Computer Science, or equivalent degree 10+ years of hands-on experience in Data Warehouse, ETL, Data Modeling & Reporting 7+ years of hands-on experience in productionizing and deploying Big Data platforms and applications, Hands-on experience working with: Relational/SQL, distributed columnar data stores/NoSQL databases, time-series databases, Spark streaming, Kafka, Hive, Delta Parquet, Avro, and more Extensive experience in understanding a variety of complex business use cases and modeling the data in the data warehouse Highly skilled in SQL, Python, Spark, AWS S3, Hive Data Catalog, Parquet, Redshift, Airflow, and Tableau or similar tools Proven experience in building a Custom Enterprise Data Warehouse or implementing tools like Data Catalogs, Spark, Tableau, Kubernetes, and Docker Knowledge of infrastructure requirements such as Networking, Storage, and Hardware Optimization with hands-on experience in Amazon Web Services (AWS) Strong verbal and written communications skills are a must and should work effectively across internal and external organizations and virtual teams Demonstrated industry leadership in the fields of Data Warehousing, Data Science, and Big Data related technologies Strong understanding of distributed systems and container-based development using Docker and Kubernetes ecosystem Deep knowledge of data structures and algorithms Experience working in large teams using CI/CD and agile methodologies Unique ID - Show more Show less

Equifax is where you can power your possible. If you want to achieve your true potential, chart new paths, develop new skills, collaborate with bright minds, and make a meaningful impact, we want to hear from you. Equifax is seeking creative, high-energy and driven software engineers with hands-on development skills to work on a variety of meaningful projects. Our software engineering positions provide you the opportunity to join a team of talented engineers working with leading-edge technology. You are ideal for this position if you are a forward-thinking, committed, and enthusiastic software engineer who is passionate about technology. What You’ll Do Demonstrate a deep understanding of cloud native, distributed micro service based architectures Deliver solutions for complex business problems through software standard SDLC Build strong relationships with both internal and external stakeholders including product, business and sales partners Demonstrate excellent communication skills with the ability to both simplify complex problems and also dive deeper if needed Build and manage strong technical teams that deliver complex software solutions that scale Manage teams with cross functional skills that include software, quality, reliability engineers, project managers and scrum masters Provide deep troubleshooting skills with the ability to lead and solve production and customer issues under pressure Leverage strong experience in full stack software development and public cloud like GCP and AWS Mentor, coach and develop junior and senior software, quality and reliability engineers Lead with a data/metrics driven mindset with a maniacal focus towards optimizing and creating efficient solutions Ensure compliance with EFX secure software development guidelines and best practices and responsible for meeting and maintaining QE, DevSec, and FinOps KPIs Define, maintain and report SLA, SLO, SLIs meeting EFX engineering standards in partnership with the product, engineering and architecture teams Collaborate with architects, SRE leads and other technical leadership on strategic technical direction, guidelines, and best practices Drive up-to-date technical documentation including support, end user documentation and run books Lead Sprint planning, Sprint Retrospectives, and other team activity Responsible for implementation architecture decision making associated with Product features/stories, refactoring work, and EOSL decisions Create and deliver technical presentations to internal and external technical and non-technical stakeholders communicating with clarity and precision, and present complex information in a concise format that is audience appropriate What Experience You Need Bachelor's degree or equivalent experience 7+ years of software engineering experience 7+ years experience writing, debugging, and troubleshooting code in mainstream Java, SpringBoot, TypeScript/JavaScript, HTML, CSS 7+ years experience with Cloud technology: GCP, AWS, or Azure 7+ years experience designing and developing cloud-native solutions 7+ years experience designing and developing microservices using Java, SpringBoot, GCP SDKs, GKE/Kubernetes 7+ years experience deploying and releasing software using Jenkins CI/CD pipelines, understand infrastructure-as-code concepts, Helm Charts, and Terraform constructs What could set you apart Self-starter that identifies/responds to priority shifts with minimal supervision. Strong communication and presentation skills Strong leadership qualities Demonstrated problem solving skills and the ability to resolve conflicts Experience creating and maintaining product and software roadmaps Experience overseeing yearly as well as product/project budgets Working in a highly regulated environment Experience designing and developing big data processing solutions using Dataflow/Apache Beam, Bigtable, BigQuery, PubSub, GCS, Composer/Airflow, and others UI development (e.g. HTML, JavaScript, Angular and Bootstrap) Experience with backend technologies such as JAVA/J2EE, SpringBoot, SOA and Microservices Source code control management systems (e.g. SVN/Git, Github) and build tools like Maven & Gradle. Agile environments (e.g. Scrum, XP) Relational databases (e.g. SQL Server, MySQL) Atlassian tooling (e.g. JIRA, Confluence, and Github) Developing with modern JDK (v1.7+) Automated Testing: JUnit, Selenium, LoadRunner, SoapUI We offer a hybrid work setting, comprehensive compensation and healthcare packages, attractive paid time off, and organizational growth potential through our online learning platform with guided career tracks. Are you ready to power your possible? Apply today, and get started on a path toward an exciting new career at Equifax, where you can make a difference! Who is Equifax? At Equifax, we believe knowledge drives progress. As a global data, analytics and technology company, we play an essential role in the global economy by helping employers, employees, financial institutions and government agencies make critical decisions with greater confidence. We work to help create seamless and positive experiences during life’s pivotal moments: applying for jobs or a mortgage, financing an education or buying a car. Our impact is real and to accomplish our goals we focus on nurturing our people for career advancement and their learning and development, supporting our next generation of leaders, maintaining an inclusive and diverse work environment, and regularly engaging and recognizing our employees. Regardless of location or role, the individual and collective work of our employees makes a difference and we are looking for talented team players to join us as we help people live their financial best. Equifax is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Show more Show less

The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers. Position : Data Scientist Location: Trivandrum (Remote or Hybrid ) Type: Full-time Start Date: Immediate Company : Turilytix.ai About the Role : Join us as a Data Scientist and work on challenging ML problems across paper manufacturing , retail, food, and IT infrastructure. Use real-world data to drive predictive intelligence with BIG-AI . Responsibilities : • Clean, engineer, and model sensor & telemetry data • Build ML models for prediction and classification • Develop explainability using SHAP, LIME • Collaborate with product/engineering to operationalize models Required Skills : • Python, Pandas, Scikit-learn • Time-series & anomaly detection • SHAP / LIME / interpretable ML • SQL, Jupyter Notebooks • Bonus: DVC, Git, Airflow Why Work With Us : • Hands-on with real-world sensor data • No red tape just impact • Remote work and global deployment • Drive AI adoption without complexity Responsibilities Analyze raw data: assessing quality, cleansing, structuring for downstream processing Design accurate and scalable prediction algorithms Collaborate with engineering team to bring analytical prototypes to production Generate actionable insights for business impSQL) Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, powerBI) Email your resume/GitHub: hr@turilytix.ai Show more Show less

You Lead the Way. We’ve Got Your Back. At American Express, we know that with the right backing, people and businesses have the power to progress in incredible ways. Whether we’re supporting our customers’ financial confidence to move ahead, taking commerce to new heights, or encouraging people to explore the world, our colleagues are constantly redefining what’s possible — and we’re proud to back each other every step of the way. When you join #TeamAmex, you become part of a diverse community of over 60,000 colleagues, all with a common goal to deliver an exceptional customer experience every day. We back our colleagues with the support they need to thrive, professionally and personally. That’s why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. We are building an energetic, high-performance team with a nimble and creative mindset to drive our technology and products. American Express (AXP) is a powerful brand, a great place to work and has unparalleled scale. Join us for an exciting opportunity in the Marketing Technology within American Express Technologies. How will you make an impact in this role? There are hundreds of opportunities to make your mark on technology and life at American Express. Here's just some of what you'll be doing: As a part of our team, you will be developing innovative, high quality, and robust operational engineering capabilities. Develop software in our technology stack which is constantly evolving but currently includes Big data, Spark, Python, Scala, GCP, Adobe Suit ( like Customer Journey Analytics ). Work with Business partners and stakeholders to understand functional requirements, architecture dependencies, and business capability roadmaps. Create technical solution designs to meet business requirements. Define best practices to be followed by team. Taking your place as a core member of an Agile team driving the latest development practices Identify and drive reengineering opportunities, and opportunities for adopting new technologies and methods. Suggest and recommend solution architecture to resolve business problems. Perform peer code review and participate in technical discussions with the team on the best solutions possible. As part of our diverse tech team, you can architect, code and ship software that makes us an essential part of our customers' digital lives. Here, you can work alongside talented engineers in an open, supportive, inclusive environment where your voice is valued, and you make your own decisions on what tech to use to solve challenging problems. American Express offers a range of opportunities to work with the latest technologies and encourages you to back the broader engineering community through open source. And because we understand the importance of keeping your skills fresh and relevant, we give you dedicated time to invest in your professional development. Find your place in technology of #TeamAmex. Minimum Qualifications: · BS or MS degree in computer science, computer engineering, or other technical discipline, or equivalent work experience. · 5+ years of hands-on software development experience with Big Data & Analytics solutions – Hadoop Hive, Spark, Scala, Hive, Python, shell scripting, GCP Cloud Big query, Big Table, Airflow. · Working knowledge of Adobe suit like Adobe Experience Platform, Adobe Customer Journey Analytics, CDP. · Proficiency in SQL and database systems, with experience in designing and optimizing data models for performance and scalability. · Design and development experience with Kafka, Real time ETL pipeline, API is desirable. · Experience in designing, developing, and optimizing data pipelines for large-scale data processing, transformation, and analysis using Big Data and GCP technologies. · Certifications in cloud platform (GCP Professional Data Engineer) is a plus. · Understanding of distributed (multi-tiered) systems, data structures, algorithms & Design Patterns. · Strong Object-Oriented Programming skills and design patterns. · Experience with CICD pipelines, Automated test frameworks, and source code management tools (XLR, Jenkins, Git, Maven). · Good knowledge and experience with configuration management tools like GitHub · Ability to analyze complex data engineering problems, propose effective solutions, and implement them effectively. · Looks proactively beyond the obvious for continuous improvement opportunities. · Communicates effectively with product and cross functional team. We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations. Show more Show less

Company Name- Interbiz Consulting Pvt Ltd Position/Designation- Data Engineer Job Location- Raipur (C.G.) Mode- Work from office Experience- 2 to 5 Years We are seeking a talented and detail-oriented Data Engineer to join our growing Data & Analytics team. You will be responsible for building and maintaining robust, scalable data pipelines and infrastructure to support data-driven decision-making across the organization. Key Responsibilities Design and implement ETL/ELT data pipelines for structured and unstructured data using Azure Data Factory , Databricks , or Apache Spark . Work with Azure Blob Storage , Data Lake , and Synapse Analytics to build scalable data lakes and warehouses. Develop real-time data ingestion pipelines using Apache Kafka , Apache Flink , or Apache Beam . Build and schedule jobs using orchestration tools like Apache Airflow or Dagster . Perform data modeling using Kimball methodology for building dimensional models in Snowflake or other data warehouses. Implement data versioning and transformation using DBT and Apache Iceberg or Delta Lake . Manage data cataloging and lineage using tools like Marquez or Collibra . Collaborate with DevOps teams to containerize solutions using Docker , manage infrastructure with Terraform , and deploy on Kubernetes . Setup and maintain monitoring and alerting systems using Prometheus and Grafana for performance and reliability. Required Skills and Qualifications Qualifications Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field. [1–5+] years of experience in data engineering or related roles. Proficiency in Python , with strong knowledge of OOP and data structures & algorithms . Comfortable working in Linux environments for development and deployment. Strong command over SQL and understanding of relational (DBMS) and NoSQL databases. Solid experience with Apache Spark (PySpark/Scala). Familiarity with real-time processing tools like Kafka , Flink , or Beam . Hands-on experience with Airflow , Dagster , or similar orchestration tools. Deep experience with Microsoft Azure , especially Azure Data Factory , Blob Storage , Synapse , Azure Functions , etc. AZ-900 or other Azure certifications are a plus. Knowledge of dimensional modeling , Snowflake , Apache Iceberg , and Delta Lake . Understanding of modern Lakehouse architecture and related best practices. Familiarity with Marquez , Collibra , or other cataloging tools. Experience with Terraform , Docker , Kubernetes , and Jenkins or equivalent CI/CD tools. Proficiency in setting up dashboards and alerts with Prometheus and Grafana . Interested candidates may share their CV on swapna.rani@interbizconsulting.com or visit www.interbizconsulting.com Note:- Immediate joiner will be preferred. Job Type: Full-time Pay: From ₹25,000.00 per month Benefits: Food provided Health insurance Leave encashment Provident Fund Supplemental Pay: Yearly bonus Application Question(s): Do you have at least 2 years of work experience in Python? Do you have at least 2 years of work experience in Data Science? Are you from Raipur, Chhattisgarh? Are you willing to work for more than 2 years? What is your notice period? What is your current salary and what you are expecting? Work Location: In person

HR Contact No. 6395012950 Job Title: Design Engineer – HVAC Manufacturing Location: Gujarat Department: Engineering/Design Reports To: MD Job Type: Full-Time Position Overview: We are seeking a talented and detail-oriented Design Engineer to join our engineering team in a dynamic HVAC manufacturing environment. The ideal candidate will have a strong background in mechanical design, proficiency in AutoCAD , and hands-on experience with nesting software for sheet metal fabrication. This role is critical to the development and production of high-quality HVAC components and systems, supporting product design, customization, and manufacturing optimization. Key Responsibilities: Design HVAC components and assemblies using AutoCAD/Nesting based on project specifications. Create and manage detailed 2D and 3D drawings, BOMs, and technical documentation. Prepare nesting layouts using nesting software for sheet metal cutting operations. Collaborate with production and fabrication teams to ensure manufacturability and cost-efficiency of designs. Modify and improve existing designs to meet performance and production requirements. Work with the Customers and Sales team to develop a quotable/manufacturing solution to the customer request. Ensure timely output drawings for customer approval Participate in new product development and R&D initiatives. Visiting Project sites as per requirement. Ensure all designs comply with industry standards and company quality procedures. Assist in resolving manufacturing and assembly issues related to design. Required Qualifications: Diploma or Bachelor's Degree in Mechanical Engineering, Manufacturing Engineering, or related field. Minimum of 2–5 years of experience in a design engineering role within a manufacturing environment, preferably HVAC. Proficiency in AutoCAD (2D required, 3D is a plus). Hands-on experience with nesting software (e.g., SigmaNEST, NestFab, or similar). Solid understanding of sheet metal fabrication processes and design principles. Strong analytical, problem-solving, and communication skills. Ability to interpret technical drawings and specifications. Experience working in a cross-functional team environment. Preferred Qualifications: Familiarity with HVAC system components and airflow principles. Experience with additional CAD/CAM software (e.g., SolidWorks, Inventor). Knowledge of lean manufacturing or value engineering practices. Job Type: Full-time Pay: ₹15,000.00 - ₹20,000.00 per month Benefits: Paid time off Provident Fund Schedule: Day shift Supplemental Pay: Yearly bonus Work Location: In person

Title: Data Engineer Location: Baner, Pune (Hybrid) 6 to 12 Months contract Responsibilities: Design, develop, and execute robust scalable data pipelines to extract, transform, and load data from on-premises SQL Server databases to GCP Cloud SQL PostgreSQL. Analyze existing SQL Server schemas, data types, and stored procedures, and plan for their conversion and optimization for the PostgreSQL environment. Implement and support data migration strategies from on-premise or legacy systems to cloud environments, primarily GCP. Implement rigorous data validation and quality checks before, during, and after migration to ensure data integrity and consistency. Collaborate closely with Database Administrators, application developers, and business analysts to understand source data structures and target requirements. Develop and maintain scripts (primarily Python or Java) for automating migration tasks, data validation, and post-migration data reconciliation. Identify and resolve data discrepancies, performance bottlenecks, and technical challenges encountered during the migration process. Document migration strategies, data mapping, transformation rules, and post-migration validation procedures. Support cutover activities and ensure minimal downtime during the transition phase. Apply data governance, security, and privacy standards across data assets in the cloud. Refactor SQL Server stored procedures and business logic for implementation in PostgreSQL or application layer where applicable. Leverage schema conversion tools (e.g., pgLoader, custom scripts) to automate and validate schema translation from SQL Server to PostgreSQL. Develop automated data validation and reconciliation scripts to ensure row-level parity and business logic integrity post-migration. Implement robust monitoring, logging, and alerting mechanisms to ensure pipeline reliability and quick failure resolution using GCP-native tools (e.g., Stackdriver/Cloud Monitoring). Must-Have Skills: Expert-level SQL proficiency across T-SQL (SQL Server) and PostgreSQL with strong hands-on experience in data transformation, query optimization, and relational database design. Solid understanding and hands-on experience working with Relational Databases. Strong experience in data engineering, with hands-on work on cloud, preferrably GCP. Experience with data migration techniques and strategies between different relational database platforms. Hands-on experience on any Cloud Data and Monitoring services such as Relational Database services, Data Pipeline services, Logging and monitoring services, - with one of the cloud providers - GCP, AWS or Azure. Experience with Python or Java for building and managing data pipelines with proficiency in data manipulation, scripting, and automation of data processes. Familiarity with ETL/ELT processes and orchestration tools like Cloud Composer (Airflow). Understanding of data modeling and schema design. Strong analytical and problem-solving skills, with a keen eye for data quality and integrity Experience with version control systems like Git. Good-to-Have Skills Exposure to database migration tools or services (e.g., AWS DMS, GCP Database Migration Service, or similar). Experience with real-time data processing using Pub/Sub. Experience with shell scripting. Exposure to CI/CD pipelines for deploying and maintaining data workflows. Familiarity with NoSQL databases and other GCP data services (e.g., Firestore, Bigtable). Show more Show less

Experience 3 to 10 Years Required Qualifications: Data Engineering Skills 3–5 years of experience in data engineering, with hands-on experience in Snowflake and basic to intermediate proficiency in dbt. Capable of building and maintaining ELT pipelines using dbt and Snowflake, with guidance on architecture and best practices. Understanding of ELT principles and foundational knowledge of data modeling techniques (preferably Kimball/Dimensional). Intermediate experience with SAP Data Services (SAP DS), including extracting, transforming, and integrating data from legacy systems. Proficient in SQL for data transformation and basic performance tuning in Snowflake (e.g., clustering, partitioning, materializations). Familiar with workflow orchestration tools like dbt Cloud, Airflow, or Control M. Experience using Git for version control and exposure to CI/CD workflows in team environments. Exposure to cloud storage solutions such as Azure Data Lake, AWS S3, or GCS for ingestion and external staging in Snowflake. Working knowledge of Python for basic automation and data manipulation tasks. Understanding of Snowflake's role-based access control (RBAC), data security features, and general data privacy practices like GDPR. Key Responsibilities Design and build robust ELT pipelines using dbt on Snowflake, including ingestion from relational databases, APIs, cloud storage, and flat files. Reverse-engineer and optimize SAP Data Services (SAP DS) jobs to support scalable migration to cloud-based data platforms. Implement layered data architectures (e.g., staging, intermediate, mart layers) to enable reliable and reusable data assets. Enhance dbt/Snowflake workflows through performance optimization techniques such as clustering, partitioning, query profiling, and efficient SQL design. Use orchestration tools like Airflow, dbt Cloud, and Control-M to schedule, monitor, and manage data workflows. Apply modular SQL practices, testing, documentation, and Git-based CI/CD workflows for version-controlled, maintainable code. Collaborate with data analysts, scientists, and architects to gather requirements, document solutions, and deliver validated datasets. Contribute to internal knowledge sharing through reusable dbt components and participate in Agile ceremonies to support consulting delivery. Skills: workflow orchestration,git,airflow,sql,gcs,elt pipelines,azure data lake,data modeling,ci/cd,dbt,cloud storage,ci,snowflake,data security,python,sap data services,data engineering,aws s3 Show more Show less

AI/ML Engineer – Senior Consultant AI Engineering Group is part of Data Science & AI Competency Center and is focusing technical and engineering aspects of DS/ML/AI solutions. We are looking for experienced AI/ML Engineers to join our team to help us bring AI/ML solutions into production, automate processes, and define reusable best practices and accelerators. Duties description: The person we are looking for will become part of DataScience and AI Competency Center working in AI Engineering team. The key duties are: Building high-performing, scalable, enterprise-grade ML/AI applications in cloud environment Working with Data Science, Data Engineering and Cloud teams to implement Machine Learning models into production Practical and innovative implementations of ML/AI automation, for scale and efficiency Design, delivery and management of industrialized processing pipelines Defining and implementing best practices in ML models life cycle and ML operations Implementing AI/MLOps frameworks and supporting Data Science teams in best practices Gathering and applying knowledge on modern techniques, tools and frameworks in the area of ML Architecture and Operations Gathering technical requirements & estimating planned work Presenting solutions, concepts and results to internal and external clients Being Technical Leader on ML projects, defining task, guidelines and evaluating results Creating technical documentation Supporting and growing junior engineers Must have skills: Good understanding of ML/AI concepts: types of algorithms, machine learning frameworks, model efficiency metrics, model life-cycle, AI architectures Good understanding of Cloud concepts and architectures as well as working knowledge with selected cloud services, preferably GCP Experience in programming ML algorithms and data processing pipelines using Python At least 6-8 years of experience in production ready code development Experience in designing and implementing data pipelines Practical experience with implementing ML solutions on GCP Vertex.AI and/or Databricks Good communication skills Ability to work in team and support others Taking responsibility for tasks and deliverables Great problem-solving skills and critical thinking Fluency in written and spoken English. Nice to have skills & knowledge: Practical experience with other programming languages: PySpark, Scala, R, Java Practical experience with tools like AirFlow, ADF or Kubeflow Good understanding of CI/CD and DevOps concepts, and experience in working with selected tools (preferably GitHub Actions, GitLab or Azure DevOps) Experience in applying and/or defining software engineering best practices Experience productization ML solutions using technologies like Docker/Kubernetes We Offer: Stable employment. On the market since 2008, 1300+ talents currently on board in 7 global sites. 100% remote. Flexibility regarding working hours. Full-time position Comprehensive online onboarding program with a “Buddy” from day 1. Cooperation with top-tier engineers and experts. Internal Gallup Certified Strengths Coach to support your growth. Unlimited access to the Udemy learning platform from day 1. Certificate training programs. Lingarians earn 500+ technology certificates yearly. Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110+ training opportunities yearly. Grow as we grow as a company. 76% of our managers are internal promotions. A diverse, inclusive, and values-driven community. Autonomy to choose the way you work. We trust your ideas. Create our community together. Refer your friends to receive bonuses. Activities to support your well-being and health. Plenty of opportunities to donate to charities and support the environment. Please click on this link to submit your application: https://system.erecruiter.pl/FormTemplates/RecruitmentForm.aspx?WebID=ac709bd295cc4008af7d0a7a0e465818 Show more Show less

Design and develop data pipelines for Generative AI projects by leveraging a combination of technologies, including Vector DB, Graph DB, Airflow, Spark, PySpark, Python, LangChain, AWS Functions, Redshift, and SSIS. This will involve the logical and efficient integration of these tools to create seamless, high-performance data flows that efficiently support the data requirements of our cutting-edge AI initiatives. Collaborate with data scientists, AI researchers, and other stakeholders to understand data requirements and translate them into effective data engineering solutions. User will be managing movement, organization and quality assessments of large set of data to facilitate the creation of Knowledge base for RAG systems and model training Demonstrate familiarity with data integration services such as AWS Glue and Azure Data Factory, showcasing the ability to effectively utilize these platforms for seamless data ingestion, transformation, and orchestration across various sources and destinations. Possess proficiency in constructing data warehouses and data lakes, demonstrating a strong foundation in organizing and consolidating large volumes of structured and unstructured data for efficient storage, retrieval, and analysis. Optimize and maintain data pipelines to ensure high-performance, reliable, and scalable data processing. Develop and implement data validation and quality assurance procedures to ensure the accuracy and consistency of the data used in Generative AI projects. Monitor and troubleshoot data pipeline performance, identify bottlenecks, and implement improvements as necessary. Stay current with emerging trends and technologies in the fields of data engineering, Generative AI, and related areas to ensure the continued success of our projects. Collaborate with team members on documentation, knowledge sharing, and best practices for data engineering within a Generative AI context. Ensure data privacy and security compliance in accordance with industry standards and regulations. Qualifications we seek in you: Bachelors or Masters degree in Computer Science, Engineering, or a related field. Strong experience with data engineering technologies, including Vector DB, Graph DB, Airflow, Spark, PySpark, Python, langchain, AWS Functions, Redshift, and SSIS. Strong understanding of data warehousing concepts, ETL processes, and data modeling. Strong understanding of S3 and code-based scripting to move large volumes of data across application storage layers Familiarity with Generative AI concepts and technologies, such as GPT-4, Transformers, and other natural language processing techniques. Excellent problem-solving, analytical, and critical thinking skills. Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams. Preferred Qualifications/ skills Knowledge of cloud computing platforms, such as AWS, Azure, or Google Cloud Platform, is a plus. Experience with big data technologies, such as Hadoop, Hive, or Presto, is a plus. Familiarity with machine learning frameworks, such as TensorFlow or PyTorch, is a plus. A continuous learning mindset and a passion for staying up-to-date with the latest advancements in data engineering and Generative AI.

Design and develop data pipelines for Generative AI projects by leveraging a combination of technologies, including Vector DB, Graph DB, Airflow, Spark, PySpark, Python, LangChain, AWS Functions, Redshift, and SSIS. This will involve the logical and efficient integration of these tools to create seamless, high-performance data flows that efficiently support the data requirements of our cutting-edge AI initiatives. Collaborate with data scientists, AI researchers, and other stakeholders to understand data requirements and translate them into effective data engineering solutions. User will be managing movement, organization and quality assessments of large set of data to facilitate the creation of Knowledge base for RAG systems and model training Demonstrate familiarity with data integration services such as AWS Glue and Azure Data Factory, showcasing the ability to effectively utilize these platforms for seamless data ingestion, transformation, and orchestration across various sources and destinations. Possess proficiency in constructing data warehouses and data lakes, demonstrating a strong foundation in organizing and consolidating large volumes of structured and unstructured data for efficient storage, retrieval, and analysis. Optimize and maintain data pipelines to ensure high-performance, reliable, and scalable data processing. Develop and implement data validation and quality assurance procedures to ensure the accuracy and consistency of the data used in Generative AI projects. Monitor and troubleshoot data pipeline performance, identify bottlenecks, and implement improvements as necessary. Stay current with emerging trends and technologies in the fields of data engineering, Generative AI, and related areas to ensure the continued success of our projects. Collaborate with team members on documentation, knowledge sharing, and best practices for data engineering within a Generative AI context. Ensure data privacy and security compliance in accordance with industry standards and regulations. Qualifications we seek in you: Bachelors or Masters degree in Computer Science, Engineering, or a related field. Strong experience with data engineering technologies, including Vector DB, Graph DB, Airflow, Spark, PySpark, Python, langchain, AWS Functions, Redshift, and SSIS. Strong understanding of data warehousing concepts, ETL processes, and data modeling. Strong understanding of S3 and code-based scripting to move large volumes of data across application storage layers Familiarity with Generative AI concepts and technologies, such as GPT-4, Transformers, and other natural language processing techniques. Excellent problem-solving, analytical, and critical thinking skills. Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams. Preferred Qualifications/ skills Knowledge of cloud computing platforms, such as AWS, Azure, or Google Cloud Platform, is a plus. Experience with big data technologies, such as Hadoop, Hive, or Presto, is a plus. Familiarity with machine learning frameworks, such as TensorFlow or PyTorch, is a plus. A continuous learning mindset and a passion for staying up-to-date with the latest advancements in data engineering and Generative AI.

Job Title: Data Engineer – Databricks, Delta Live Tables, Data Pipelines Location: Bhopal / Hyderabad / Pune (On-site) Experience Required: 5+ Years Employment Type: Full-Time Job Summary: We are seeking a skilled and experienced Data Engineer with a strong background in designing and building data pipelines using Databricks and Delta Live Tables. The ideal candidate should have hands-on experience in managing large-scale data engineering workloads and building scalable, reliable data solutions in cloud environments. Key Responsibilities: Design, develop, and manage scalable and efficient data pipelines using Databricks and Delta Live Tables . Work with structured and unstructured data to enable analytics and reporting use cases. Implement data ingestion , transformation , and cleansing processes. Collaborate with Data Architects, Analysts, and Data Scientists to ensure data quality and integrity. Monitor data pipelines and troubleshoot issues to ensure high availability and performance. Optimize queries and data flows to reduce costs and increase efficiency. Ensure best practices in data security, governance, and compliance. Document architecture, processes, and standards. Required Skills: Minimum 5 years of hands-on experience in data engineering . Proficient in Apache Spark , Databricks , Delta Lake , and Delta Live Tables . Strong programming skills in Python or Scala . Experience with cloud platforms such as Azure , AWS , or GCP . Proficient in SQL for data manipulation and analysis. Experience with ETL/ELT pipelines , data wrangling , and workflow orchestration tools (e.g., Airflow, ADF). Understanding of data warehousing , big data ecosystems , and data modeling concepts. Familiarity with CI/CD processes in a data engineering context. Nice to Have: Experience with real-time data processing using tools like Kafka or Kinesis. Familiarity with machine learning model deployment in data pipelines. Experience working in an Agile environment. Show more Show less

Job Title: Sr. Data Engineer Location: Office-Based (Ahmedabad, India) About Hitech Hitech is a leading provider of Data, Engineering Services, and Business Process Solutions. With robust delivery centers in India and global sales offices in the USA, UK, and the Netherlands, we enable digital transformation for clients across industries including Manufacturing, Real Estate, and e-Commerce. Our Data Solutions practice integrates automation, digitalization, and outsourcing to deliver measurable business outcomes. We are expanding our engineering team and looking for an experienced Sr. Data Engineer to design scalable data pipelines, support ML model deployment, and enable insight-driven decisions. Position Summary We are seeking a Data Engineer / Lead Data Engineer with deep experience in data architecture, ETL pipelines, and advanced analytics support. This role is crucial for designing robust pipelines to process structured and unstructured data, integrate ML models, and ensure data reliability. The ideal candidate will be proficient in Python, R, SQL, and cloud-based tools, and possess hands-on experience in creating end-to-end data engineering solutions that support data science and analytics teams. Key Responsibilities Design and optimize data pipelines to ingest, transform, and load data from diverse sources. Build programmatic ETL pipelines using SQL and related platforms. Understand complex data structures and perform data transformation effectively. Develop and support ML models such as Random Forest, SVM, Clustering, Regression, etc. Create and manage scalable, secure data warehouses and data lakes. Collaborate with data scientists to structure data for analysis and modeling. Define solution architecture for layered data stacks ensuring high data quality. Develop design artifacts including data flow diagrams, models, and functional documents. Work with technologies such as Python, R, SQL, MS Office, and SageMaker. Conduct data profiling, sampling, and testing to ensure reliability. Collaborate with business stakeholders to identify and address data use cases. Qualifications & Experience 4 to 6 years of experience in data engineering, ETL development, or database administration. Bachelor’s degree in Mathematics, Computer Science, or Engineering (B.Tech/B.E.). Postgraduate qualification in Data Science or related discipline preferred. Strong proficiency in Python, SQL, Advanced MS Office tools, and R. Familiarity with ML concepts and integrating models into pipelines. Experience with NoSQL systems like MongoDB, Cassandra, or HBase. Knowledge of Snowflake, Databricks, and other cloud-based data tools. ETL tool experience and understanding of data integration best practices. Data modeling skills for relational and NoSQL databases. Knowledge of Hadoop, Spark, and scalable data processing frameworks. Experience with SciKit, TensorFlow, Pytorch, GPT, PySpark, etc. Ability to build web scrapers and collect data from APIs. Experience with Airflow or similar tools for pipeline automation. Strong SQL performance tuning skills in large-scale environments. What We Offer Competitive compensation package based on skills and experience. Opportunity to work with international clients and contribute to high-impact data projects. Continuous learning and professional growth within a tech-forward organization. Collaborative and inclusive work environment. If you're passionate about building data-driven infrastructure to fuel analytics and AI applications, we look forward to connecting with you. Anand Soni Hitech Digital Solutions Show more Show less

About US At Particleblack, we drive innovation through intelligent experimentation with Artificial Intelligence. Our multidisciplinary team—comprising solution architects, data scientists, engineers, product managers, and designers—collaborates with domain experts to deliver cutting-edge R&D solutions tailored to your business. Our ecosystem empowers rapid execution with plug-and-play tools, enabling scalable, AI-powered strategies that fast-track your digital transformation. With a focus on automation and seamless integration, we help you stay ahead—letting you focus on your core, while we accelerate your growth Responsibilities & Qualifications Data Architecture Design: Develop and implement scalable and efficient data architectures for batch and real-time data processing.Design and optimize data lakes, warehouses, and marts to support analytical and operational use cases. ETL/ELT Pipelines: Build and maintain robust ETL/ELT pipelines to extract, transform, and load data from diverse sources.Ensure pipelines are highly performant, secure, and resilient to handle large volumes of structured and semi-structured data. Data Quality and Governance: Establish data quality checks, monitoring systems, and governance practices to ensure the integrity, consistency, and security of data assets. Implement data cataloging and lineage tracking for enterprise-wide data transparency. Collaboration with Teams:Work closely with data scientists and analysts to provide accessible, well-structured datasets for model development and reporting. Partner with software engineering teams to integrate data pipelines into applications and services. Cloud Data Solutions: Architect and deploy cloud-based data solutions using platforms like AWS, Azure, or Google Cloud, leveraging services such as S3, BigQuery, Redshift, or Snowflake. Optimize cloud infrastructure costs while maintaining high performance. Data Automation and Workflow Orchestration: Utilize tools like Apache Airflow, n8n, or similar platforms to automate workflows and schedule recurring data jobs. Develop monitoring systems to proactively detect and resolve pipeline failures. Innovation and Leadership: Research and implement emerging data technologies and methodologies to improve team productivity and system efficiency. Mentor junior engineers, fostering a culture of excellence and innovation.| Required Skills: Experience: 7+ years of overall experience in data engineering roles, with at least 2+ years in a leadership capacity. Proven expertise in designing and deploying large-scale data systems and pipelines. Technical Skills: Proficiency in Python, Java, or Scala for data engineering tasks. Strong SQL skills for querying and optimizing large datasets. Experience with data processing frameworks like Apache Spark, Beam, or Flink. Hands-on experience with ETL tools like Apache NiFi, dbt, or Talend. Experience in pub sub and stream processing using Kafka/Kinesis or the like Cloud Platforms: Expertise in one or more cloud platforms (AWS, Azure, GCP) with a focus on data-related services. Data Modeling: Strong understanding of data modeling techniques (dimensional modeling, star/snowflake schemas). Collaboration: Proven ability to work with cross-functional teams and translate business requirements into technical solutions. Preferred Skills: Familiarity with data visualization tools like Tableau or Power BI to support reporting teams. Knowledge of MLOps pipelines and collaboration with data scientists. Show more Show less

Senior Data Engineer (Contract) Location: Bengaluru, Karnataka, India About the Role: We're looking for an experienced Senior Data Engineer (6-8 years) to join our data team. You'll be key in building and maintaining our data systems on AWS. You'll use your strong skills in big data tools and cloud technology to help our analytics team get valuable insights from our data. You'll be in charge of the whole process of our data pipelines, making sure the data is good, reliable, and fast. What You'll Do: Design and build efficient data pipelines using Spark / PySpark / Scala . Manage complex data processes with Airflow , creating and fixing any issues with the workflows ( DAGs ). Clean, transform, and prepare data for analysis. Use Python for data tasks, automation, and building tools. Work with AWS services like S3, Redshift, EMR, Glue, and Athena to manage our data infrastructure. Collaborate closely with the Analytics team to understand what data they need and provide solutions. Help develop and maintain our Node.js backend, using Typescript , for data services. Use YAML to manage the settings for our data tools. Set up and manage automated deployment processes ( CI/CD ) using GitHub Actions . Monitor and fix problems in our data pipelines to keep them running smoothly. Implement checks to ensure our data is accurate and consistent. Help design and build data warehouses and data lakes. Use SQL extensively to query and work with data in different systems. Work with streaming data using technologies like Kafka for real-time data processing. Stay updated on the latest data engineering technologies. Guide and mentor junior data engineers. Help create data management rules and procedures. What You'll Need: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 6-8 years of experience as a Data Engineer. Strong skills in Spark and Scala for handling large amounts of data. Good experience with Airflow for managing data workflows and understanding DAGs . Solid understanding of how to transform and prepare data. Strong programming skills in Python for data tasks and automation.. Proven experience working with AWS cloud services (S3, Redshift, EMR, Glue, IAM, EC2, and Athena ). Experience building data solutions for Analytics teams. Familiarity with Node.js for backend development. Experience with Typescript for backend development is a plus. Experience using YAML for configuration management. Hands-on experience with GitHub Actions for automated deployment ( CI/CD ). Good understanding of data warehousing concepts. Strong database skills - OLAP/OLTP Excellent command of SQL for data querying and manipulation. Experience with stream processing using Kafka or similar technologies. Excellent problem-solving, analytical, and communication skills. Ability to work well independently and as part of a team. Bonus Points: Familiarity with data lake technologies (e.g., Delta Lake, Apache Iceberg). Experience with other stream processing technologies (e.g., Flink, Kinesis). Knowledge of data management, data quality, statistics and data governance frameworks. Experience with tools for managing infrastructure as code (e.g., Terraform). Familiarity with container technologies (e.g., Docker, Kubernetes). Experience with monitoring and logging tools (e.g., Prometheus, Grafana).

Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Databricks Unified Data Analytics Platform Good to have skills : NA Minimum 7.5 Year(s) Of Experience Is Required Educational Qualification : 15 years full time education Summary: As a Data Engineer, you will design, develop, and maintain data solutions that facilitate data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across various systems. You will collaborate with cross-functional teams to understand their data needs and provide effective solutions, ensuring that the data infrastructure is robust and scalable to meet the demands of the organization. Roles & Responsibilities: - Expected to be an SME. - Collaborate and manage the team to perform. - Responsible for team decisions. - Engage with multiple teams and contribute on key decisions. - Provide solutions to problems for their immediate team and across multiple teams. - Mentor junior team members to enhance their skills and knowledge in data engineering. - Continuously evaluate and improve data processes to enhance efficiency and effectiveness. Professional & Technical Skills: - Must To Have Skills: Proficiency in Databricks Unified Data Analytics Platform. - Experience with data pipeline orchestration tools such as Apache Airflow or similar. - Strong understanding of ETL processes and data warehousing concepts. - Familiarity with cloud platforms like AWS, Azure, or Google Cloud. - Knowledge of programming languages such as Python or Scala for data manipulation. Additional Information: - The candidate should have minimum 7.5 years of experience in Databricks Unified Data Analytics Platform. - This position is based at our Pune office. - A 15 years full time education is required. 15 years full time education Show more Show less