Responsibilities Establish scalable, efficient, automated processes for data analysis, data model development, validation, and implementation. Work closely with analysts/data scientists to understand impact to the downstream data models. Write efficient and well-organized software to ship products in an iterative, continual release environment. Contribute to and promote good software engineering practices across the team Communicate clearly and effectively to technical and non-technical audiences. Minimum Qualifications University or advanced degree in engineering, computer science, mathematics, or a related field Strong hands-on experience in Databricks using PySpark and Spark SQL (Unity Catalog, workflows, Optimization techniques) Experience with at least one cloud provider solution (GCP preferred) Strong experience working with relational SQL databases. Strong experience with object-oriented/object function scripting language : Python. Working knowledge in any transformation tools, DBT preferred. Ability to work with Linux platform. Strong knowledge of data pipeline and workflow management tools (Airflow) Working knowledge of Git hub /Git Toolkit Expertise in standard software engineering methodology, e.g. unit testing, code reviews, design documentation Experience creating Data pipelines that prepare data for ingestion & consumption appropriately. Experience in maintaining and optimizing databases/filesystems for production usage in reporting, analytics. Working in a collaborative environment and interacting effectively with technical and non-technical team members equally well. Good verbal and written communication skill (ref:hirist.tech) Show more Show less

Job Title : Java Developer Big Data Experience : 6+ Location : Bangalore | Chennai Notice Period : Immediate to 4 Weeks Job Summary We are seeking a Java Developer with 2+ years of hands-on Big Data experience to join our high-performing data engineering team. The ideal candidate should have strong Java development skills along with practical exposure to Big Data technologies and data processing frameworks. You will play a key role in building scalable, data-driven applications. Key Responsibilities Design, develop, and maintain Java-based applications that interact with Big Data ecosystems. Build scalable data pipelines using Big Data technologies (Hadoop, Spark, Hive, Kafka, etc. Collaborate with data engineers, analysts, and architects to implement data solutions. Optimize and tune data processes for performance and scalability. Develop REST APIs for data access and processing. Ensure data quality, security, and reliability across pipelines and services. Required Skills 612 years of overall experience in Java/J2EE application development. 2+ years of hands-on experience with Big Data tools like Hadoop, Spark, Hive, HBase, or Kafka. Strong experience with Spring Boot, REST APIs, and Microservices architecture. Proficient in SQL, data structures, and algorithms. Familiarity with distributed systems, batch and stream processing. Experience working with data lakes, data warehouses, or large-scale data platforms. Nice To Have Experience with Apache Airflow, Flink, or Presto. Knowledge of NoSQL databases like Cassandra or MongoDB. Exposure to cloud platforms and Big Data services. Familiarity with containerization tools like Docker, Kubernetes (ref:hirist.tech) Show more Show less

About EasyRewardz EasyRewardz is a leading customer experience management company. It provides end-to-end customer engagement solutions to 100+ brands across 3500+ retail offline stores. EasyRewardz has a presence across all key retail verticals Apparel, Fashion, Luxury, Food & Beverage, Travel and Entertainment, Wellness, and Banking. Key Capabilities Of EasyRewardzs Proprietary Technology Platform Include Customer loyalty program as an end-to-end solution. Platform for intelligent and meaningful engagement with brands customers. Analytics engine to enable brands to engage in personalized conversations with consumers. SaaS-based customer experience management solution to provide a unified view of the consumer at the multichannel level. Why EasyRewardz? Machine Learning, Personalization, Marketing Automation, Consumer Preferences these terms get real at EasyRewardz. If youre looking for a career that allows you to innovate and think differently, EasyRewardz is the place!. We are a fast-growing organization, and our journey has been fantastic shaping young minds and driving retail excellence by influencing customer behavior. Who are we seeking? Like-minded individuals with an entrepreneurial mindset, a passion to learn and excel. We value Performance and Performers. Job Title : Senior Data Engineer. Location : Gurgaon. Experience Required : 4+ years. Department : Data Engineering & Analytics. About The Role EasyRewardz is Indias leading customer engagement and loyalty platform. Our Ecosystem Includes CRM. Marketing automation. AI-powered segmentation. Campaign orchestration. Analytics. Omnichannel communication tools. Were looking for a Senior Data Engineer who can design, build, and optimize scalable data pipelines and platforms that power our product suite including Zence Marketing, Zence 360, and loyalty systems. Key Responsibilities Architect, build, and maintain real-time and batch data pipelines using tools like Apache Spark, RisingWave, Redpanda, and ScyllaDB. Collaborate with product managers, analysts, and developers to design systems that support business intelligence, behavioral analytics, and campaign automation. Own and manage data ingestion from SDKs and third-party systems via webhooks and APIs. Implement and maintain ETL/ELT pipelines across various customer touchpoints and engagement journeys. Optimize queries and data storage using ScyllaDB, MySQL, and data lakes. Ensure data quality, reliability, and governance through validation, monitoring, and alerting. Work with DevOps to deploy scalable, fault-tolerant infrastructure in cloud or hybrid environments. Mentor junior engineers and contribute to architecture and roadmap planning. Must-Have Skills Strong experience with Apache Spark, Kafka/Redpanda, RisingWave, or similar stream processing tools. Proficient in Python or Scala for pipeline scripting and data transformation. Deep understanding of data modeling, distributed databases (ScyllaDB, Cassandra), and performance optimization. Experience with both SQL and NoSQL systems (e., MySQL, ScyllaDB). Familiarity with event-driven architecture and large-scale customer event data. Solid grasp of data quality frameworks, testing, lineage, and governance. Experience with marketing automation or CRM platforms is a strong plus. Good-to-Have Skills Working knowledge of n8n, Airflow, or other orchestration frameworks. Understanding of SDK-based event capture and retry mechanisms. What We Offer Opportunity to shape the data strategy of one of Indias top Martech platforms. Collaborative and innovation-focused work environment. Flexible work hours and remote-friendly setup. Attractive compensation and clear growth path. (ref:hirist.tech) Show more Show less

About Us Lemma Technologies is a software start-up company based in Baner Pune. We are unleashing the power of programmatic AdTech to the DOOH ( Digital out of home ) world. Our Mission is to Transform Digital Out Of Home media to connect Brands with their Consumer by Establishing Authentic and Transparent Standards. Innovation is our DNA and Transparency is our RNA We are Revolutionising the DOOH industry. As an organisation, we successfully deliver brand stories seamlessly across all large format digital screens from DOOH to CTV and even on mobile and desktop devices. We are focussed on connecting DOOH media to mainstream digital, enabling brands to deploy omni-digital strategies through our platform. Roles & Responsibilities Chief Data Scientist /Architect of Lemma Technologies. This role will be responsible to define and execute the technical strategy for adoption of modern AI / ML practices to acquire, process data and provide actional insights to Lemma customers. Good understanding of the entire journey of Data acquisition, Data warehouse, Information Architecture, Dashboard, Reports, Predictive Insights, Adoption of AI / ML and NLP and provide innovative data oriented insights for Lemma customers Deep understanding of Data science and Technology and can recommend adoption of right technical tools and strategies. Expected to be hands on technical expert who will build and guide a technical data team Build, design and implement our highly scalable, fault-tolerant, highly available big data platform to process terabytes of data and provid customers with in-depth analytics. Deep data science and AI/ML hands-on experience to give actionable insights to advertisers/ customers of Lemma Good overview of modern technology stack such as Spark, Hadoop, Kafka, HBase, Hive, Presto etc. Automate high-volume data collection and processing to provide real time data analytics. Customize Lemmas reporting and analytics platform based on customers requirements from customers and deliver scalable, production-ready solutions. Lead multiple projects to develop features for data processing and reporting platform, collaborate with product managers, cross-functional teams, other stakeholders and ensure successful delivery of projects. Leveraging a broad range of Lemmas data architecture strategies and proposing both data flows and storage solutions. Managing Hadoop map reduce and spark jobs & solving any ongoing issues with operating the cluster. Working closely with cross functional teams on improving availability and scalability of large data platform and functionality of Lemma software. Participate in Agile/Scrum processes such as sprint planning, sprint retrospective, backlog grooming, user story management, work item prioritization, etc.. Skills Required 10 to 12+ years of proven experience in designing, implementing, and delivering complex, scalable, and resilient platform and services. Experience in building AI, machine learning, Data Analytics Experience in OLAP (Snowflake, Vertica or similar) would be an added advantage. Ability to understand vague business problems and convert into working solutions. Excellent spoken and written interpersonal skills with a collaborative approach. Dedication to developing high-quality software and products. Curiosity to explore and understand data is a strong plus Deep understanding of Big-Data and distributed systems (MapReduce, Spark, Hive, Kafka, Oozie, Airflow) (ref:hirist.tech) Show more Show less

Role Overview We are looking for an experienced MLOps Engineer to join our growing AI/ML team. You will be responsible for automating, monitoring, and managing machine learning workflows and infrastructure in production environments. This role is key to ensuring our AI solutions are scalable, reliable, and continuously improving. Key Responsibilities Design, build, and manage end-to-end ML pipelines, including model training, validation, deployment, and monitoring. Collaborate with data scientists, software engineers, and DevOps teams to integrate ML models into production systems. Develop and manage scalable infrastructure using AWS, particularly AWS Sagemaker. Automate ML workflows using CI/CD best practices and tools. Ensure model reproducibility, governance, and performance tracking. Monitor deployed models for data drift, model decay, and performance metrics. Implement robust versioning and model registry systems. Apply security, performance, and compliance best practices across ML systems. Contribute to documentation, knowledge sharing, and continuous improvement of our MLOps capabilities. Required Skills & Qualifications 4+ years of experience in Software Engineering or MLOps, preferably in a production environment. Proven experience with AWS services, especially AWS Sagemaker for model development and deployment. Working knowledge of AWS DataZone (preferred). Strong programming skills in Python, with exposure to R, Scala, or Apache Spark. Experience with ML model lifecycle management, version control, containerization (Docker), and orchestration tools (e.g., Kubernetes). Familiarity with MLflow, Airflow, or similar pipeline/orchestration tools. Experience integrating ML systems into CI/CD workflows using tools like Jenkins, GitHub Actions, or AWS CodePipeline. Solid understanding of DevOps and cloud-native infrastructure practices. Excellent problem-solving skills and the ability to work collaboratively across teams. (ref:hirist.tech) Show more Show less

Position : Tech Lead Data Engineer Exp : 8+ Yrs Job Location : Gurugram (3 days work from office) Mandate skill : Snowflake, Python, SQL, ETL/ELT with Asset Management experience (Finance domain) NP : with 15 - 20 days Job Description Key Responsibilities : Data Pipeline Development : Design, build, and maintain robust ELT (Extract, Load, Transform) pipelines using Snowflake to support data ingestion, integration, and transformation. Technical Leadership : Lead offshore development teams in implementing best practices for data engineering and ELT development. Data Integration : Collaborate with stakeholders to understand data sources and integration requirements, ensuring seamless connectivity and data flow between systems. Performance Optimization : Optimize data pipelines for performance, scalability, and reliability, including query tuning and resource management within Snowflake. Data Quality Assurance : Implement and monitor data validation procedures to ensure data accuracy and consistency across systems. Collaboration and Communication : Work closely with project managers, data architects, and business analysts to align project milestones and deliverables with business goals. Documentation : Create and maintain detailed documentation of data pipelines, data flow diagrams, and transformation logic. Issue Resolution : Troubleshoot and resolve issues related to data pipelines, including job failures and performance bottlenecks. Compliance and Security : Ensure all data management processes comply with data governance policies and regulatory requirements in financial services. Required Qualifications Bachelors degree in Computer Science, Information Technology, or a related field. 5+ years of experience in data engineering with a strong focus on ELT processes and data pipeline development. Hands-on experience with Snowflake cloud data platform, including data sharing, secure views, and performance optimization. Proficiency in SQL and familiarity with data integration and ETL/ELT tools. Experience managing and collaborating with offshore development teams. Strong problem-solving skills and the ability to work independently to meet deadlines. Excellent communication skills for effectively interacting with technical and non-technical stakeholders. Preferred Qualifications Certifications in Snowflake or relevant data technologies. Experience in the financial services sector with an understanding of data security and compliance requirements. Familiarity with cloud platforms (e.g., AWS, Azure) and data orchestration tools (e.g., Apache Airflow). Experience with scripting languages such as Python or JavaScript for data transformation. Knowledge of data visualization tools (e.g., Tableau, Power BI) (ref:hirist.tech) Show more Show less

We are looking for a highly skilled Generative AI Developer : Responsibilities We are looking for a highly skilled Generative AI Developer with expertise in Large Language Models (LLMs) to join our AI/ML innovation team. The ideal candidate will be responsible for building, fine-tuning, deploying, and optimizing generative AI models to solve complex real-world problems. You will collaborate with data scientists, machine learning engineers, product managers, and software developers to drive forward next-generation AI-powered Responsibilities : Design and develop AI-powered applications using large language models (LLMs) such as GPT, LLaMA, Mistral, Claude, or similar. Fine-tune pre-trained LLMs for specific tasks (e.g., text summarization, Q&A systems, chatbots, semantic search). Build and integrate LLM-based APIs into products and systems. Optimize inference performance, latency, and throughput of LLMs for deployment at scale. Conduct prompt engineering and design strategies for prompt optimization and output consistency. Develop evaluation frameworks to benchmark model quality, response accuracy, safety, and bias. Manage training data pipelines and ensure data privacy, compliance, and quality standards. Experiment with open-source LLM frameworks and contribute to internal libraries and tools. Collaborate with MLOps teams to automate deployment, CI/CD pipelines, and monitoring of LLM solutions. Stay up to date with state-of-the-art advancements in generative AI, NLP, and foundation Skills Required : LLMs & Transformers: Deep understanding of transformer-based architectures (e.g., GPT, BERT, T5, LLaMA, Falcon). Model Training/Fine-Tuning: Hands-on experience with training/fine-tuning large models using libraries such as Hugging Face Transformers, DeepSpeed, LoRA, PEFT. Prompt Engineering: Expertise in designing, testing, and refining prompts for specific tasks and outcomes. Python: Strong proficiency in Python with experience in ML and NLP libraries. Frameworks: Experience with PyTorch, TensorFlow, Hugging Face, LangChain, or similar frameworks. MLOps: Familiarity with tools like MLflow, Kubeflow, Airflow, or SageMaker for model lifecycle management. Data Handling: Experience with data pipelines, preprocessing, and working with structured and unstructured Desirable Skills : Deployment: Knowledge of deploying LLMs on cloud platforms like AWS, GCP, Azure, or edge devices. Vector Databases: Experience with FAISS, Pinecone, Weaviate, or ChromaDB for semantic search applications. LLM APIs: Experience integrating with APIs like OpenAI, Cohere, Anthropic, Mistral, etc. Containerization: Docker, Kubernetes, and cloud-native services for scalable model deployment. Security & Ethics: Understanding of LLM security, hallucination handling, and responsible AI : Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or related field. 2-4 years of experience in ML/NLP roles with at least 12 years specifically focused on generative AI and LLMs. Prior experience working in a research or product-driven AI team is a plus. Strong communication skills to explain technical concepts and findings Skills : Analytical thinker with a passion for solving complex problems. Team player who thrives in cross-functional settings. Self-driven, curious, and always eager to learn the latest advancements in AI. Ability to work independently and deliver high-quality solutions under tight deadlines. (ref:hirist.tech) Show more Show less

We are looking for a highly skilled Big Data Engineer with expertise in cloud technologies to join our team. The ideal candidate will be responsible for designing, developing, and maintaining scalable big data solutions, ensuring efficient data processing, storage, and analytics. This role involves working with distributed systems, cloud platforms, and modern data frameworks to support real-time and batch data pipelines. The above-mentioned skillsets or roles are used for creating content and labs. Responsibilities Design, implement, and manage scalable big data architectures on AWS, Azure, or GCP. Develop ETL pipelines for ingesting, processing, and transforming large datasets. Work with Python, Apache Spark, Hadoop, and Kafka to build efficient data processing solutions. Implement data lakes, data warehouses, and streaming architectures. Optimize database and query performance for large-scale datasets. Collaborate with SMEs, Clients, and software engineers to deliver content. Ensure data security, governance, and compliance with industry standards. Automate workflows using Apache Airflow or other orchestration tools. Monitor and troubleshoot data pipelines to ensure reliability and scalability. Requirements Minimum educational qualifications: B. E., B. Sc, M. Sc, MCA Proficiency in Python, Java, or Scala for data processing. Hands-on experience with Apache Spark, Hadoop, Kafka, Flink, Storm. Hands-on experience working with SQL and NoSQL databases. Strong expertise in cloud-based data solutions (AWS / Google / Azure). Hands-on experience in building and managing ETL/ELT pipelines. Knowledge of containerization and orchestration, Docker or K8S. Hands-on with real-time data streaming and serverless data processing. Familiarity with machine learning pipelines and AI-driven analytics. Strong understanding of CI/CD & ETL pipelines for data workflows. Technical Skills Big Data Technologies: Apache Spark, Hadoop, Kafka, Flink, Storm. Cloud Platforms: AWS / Google / Azure. Programming Languages: Python, Java, Scala, SQL, PySpark. Data Storage and Processing: Data Lakes, Warehouses, ETL/ELT Pipelines. Orchestration: Apache Airflow, Prefect, Dagster. Databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Cassandra). Security and Compliance: IAM, Data Governance, Encryption. DevOps Tools: Docker, Kubernetes, Terraform, CI/CD Pipelines. Soft Skills Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Ability to work in an agile, fast-paced environment. Attention to detail and data accuracy. Self-motivated and proactive. Certifications Any Cloud or Data-related certifications. (ref:hirist.tech) Show more Show less

We are seeking a highly skilled MLOps Engineer with experience in Healthcare domain to join our team. The Engineer will be responsible for ensuring the accuracy, performance, and stability of ML models. This role includes continuous monitoring, maintenance, and improvement of ML pipelines, Docker images, and data synchronization processes. Key Responsibilities Model Accuracy & Performance : Perform in-depth analysis of model accuracy. Identify and diagnose issues affecting model accuracy. Collaborate with data scientists to address and rectify model shortcomings. Regularly compare model performance against previous results to identify trends and improvement & Infrastructure Maintenance: Design and implement cloud solutions for MLOps (AWS, Azure, or GCP). Build and maintain CI/CD pipelines using GitLab CI, GitHub Actions, Circle CI, Airflow, or similar tools. Maintain production pipelines and Docker images with the latest model code. Ensure stability and alignment between development and production environments. Model Deployment & Monitoring Manage containerization, deployment, versioning, and monitoring of ML models. Implement automated testing, validation, and quality checks for data science models. Troubleshoot and resolve bugs related to model deployment and data synchronization. Data Synchronization & Reporting Maintain consistent data synchronization across systems. Export and format monthly results for reporting and analysis. Upload and process monthly CSV data into databases. Implement and improve event logic for data insights. Stakeholder Collaboration Provide insights and explanations for model predictions to stakeholders. Collaborate with affiliate teams to address their needs related to predictions and model outputs. Conduct deep-dive analyses on model performance, including feature importance and model : 4+ years of experience as MLOps Engineer. Minimum 2 years experience supporting Healthcare business as MLOps Engineer. Proven experience in designing and implementing cloud-based MLOps solutions (AWS, Azure, GCP). Proficiency in CI/CD pipeline orchestration tools (GitLab CI, GitHub Actions, Circle CI, Airflow). Strong programming skills in Python, Go, Ruby, or Bash. Solid understanding of Linux environments. Hands-on experience with machine learning frameworks (scikit-learn, Keras, PyTorch, TensorFlow). Familiarity with Agile project delivery processes. Strong analytical and problem-solving skills with a quality control mindset. Excellent written and verbal communication skills for effective team coordination. Consulting experience with creativity, critical thinking, project planning, and attention to detail. Knowledge of the US/Europe pharmaceutical market and experience with pharmaceutical data is a plus. Number of Positions : 2. Job Type : Full-Time. Experience Required : 4+ Years (Mandatory: Healthcare Domain experience of 2 years). Location : Gurgaon. Work Mode : Onsite. Shift : UK Shift. (ref:hirist.tech) Show more Show less

About The Company Veersa is a healthtech company that leverages emerging technology and data science to solve business problems in the US healthcare industry. Veersa has established a niche in serving small and medium entities in the US healthcare space through its tech frameworks, platforms, and tech accelerators. Veersa is known for providing innovative solutions using technology and data science to its client base and is the preferred innovation partner to its clients. Veersas rich technology expertise manifests in the various tech accelerators and frameworks developed in-house to assist in rapid solutions delivery and implementations. Its end-to-end data ingestion, curation, transformation, and augmentation framework has helped several clients quickly derive business insights and monetize data assets. Veersa teams work across all emerging technology areas such as AI/ML, IoT, and Blockchain and using tech stacks as MEAN, MERN, PYTHON, GoLang, ROR, and backend such as Java Springboot, NodeJs, and using databases as PostgreSQL, MS SQL, MySQL, Oracle on AWS and Azure cloud using serverless architecture. Veersa has two major business lines Veersalabs : an In-house R&D and product development platform and Veersa tech consulting : Technical solutions delivery for clients. Veersas customer base includes large US Healthcare software vendors, Pharmacy chains, Payers, providers, and Hospital chains. Though Veersas focus geography is North America, Veersa also provides product engineering expertise to a few clients in Australia and Singapore. Position : SE/ Senior Data Engineer (with SQL, Python, Airflow, Bash) About The Role We are seeking a highly skilled and experienced Senior/Lead Data Engineer to join our growing Data Engineering Team. In this critical role, you will design, architect, and develop cutting-edge multi-tenant SaaS data solutions hosted on Azure Cloud. Your work will focus on delivering robust, scalable, and high-performance data pipelines and integrations that support our enterprise provider and payer data ecosystem. This role is ideal for someone with deep experience in ETL/ELT processes, data warehousing principles, and real-time and batch data integrations. As a senior member of the team, you will also be expected to mentor and guide junior engineers, help define best practices, and contribute to the overall data strategy. We are specifically looking for someone with strong hands-on experience in SQL, Python, and ideally Airflow and Bash scripting. Key Responsibilities Architect and implement scalable data integration and data pipeline solutions using Azure cloud services. Design, develop, and maintain ETL/ELT processes, including data extraction, transformation, loading, and quality checks using tools like SQL, Python, and Airflow. Build and automate data workflows and orchestration pipelines; knowledge of Airflow or equivalent tools is a plus. Write and maintain Bash scripts for automating system tasks and managing data jobs. Collaborate with business and technical stakeholders to understand data requirements and translate them into technical solutions. Develop and manage data flows, data mappings, and data quality & validation rules across multiple tenants and systems. Implement best practices for data modeling, metadata management, and data governance. Configure, maintain, and monitor integration jobs to ensure high availability and performance. Lead code reviews, mentor data engineers, and help shape engineering culture and standards. Stay current with emerging technologies and recommend tools or processes to improve the team's effectiveness. Required Qualifications Must have B.Tech or B.E degree in Computer Science, Information Systems, or any related field. 3+ years of experience in data engineering, with a strong focus on Azure-based solutions. Proficiency in SQL and Python for data processing and pipeline development. Experience in developing and orchestrating pipelines using Airflow (preferred) and writing automation scripts using Bash. Proven experience in designing and implementing real-time and batch data integrations. Hands-on experience with Azure Data Factory, Azure Data Lake, Azure Synapse, Databricks, or similar technologies. Strong understanding of data warehousing principles, ETL/ELT methodologies, and data pipeline architecture. Familiarity with data quality, metadata management, and data validation frameworks. Strong problem-solving skills and the ability to communicate complex technical concepts clearly. Preferred Qualifications Experience with multi-tenant SaaS data solutions. Background in healthcare data, especially provider and payer ecosystems. Familiarity with DevOps practices, CI/CD pipelines, and version control systems (e.g., Git). Experience mentoring and coaching other engineers in technical and architectural decision-making. (ref:hirist.tech) Show more Show less

What Youll Do Oversee the technological choices and implementation of data pipelines and warehousing strategies Design data sets that are simple, maintainable, and enable Data Analysts, Data Scientists, and stakeholders to work efficiently with data Lead cross-organizational efforts aimed at automating our data processes and data-as-a-service capabilities Advocate for and implement technical best practices throughout the data organization to ensure high-quality outcomes Mentor data team members fostering a culture of learning and continuous improvement Partner with other leaders to bring innovative concepts to reality and design data models for downstream data maximization Ensure reliability in data pipelines and enforce data governance, security, and protection of customer information while balancing technical debt. Evaluate and champion new engineering tools that enhance efficiency and scalability within the Youll Need : A Bachelor/Masters Degree in Computer Science or related field with 10+ years of experience in Data Engineering. Extensive experience with data engineering techniques, including proficiency in Python and SQL. You are acquainted with designing custom Machine Learning (ML) pipelines that integrate into production environments that are customer facing. You have experience working on product teams but also collaborating with other data science team members. You can communicate with a team and articulate ideas to both team members and non-technical stakeholders. Strong Working knowledge of Airflow, dbt, Jira, Git, and Data Warehousing tools (BigQuery, Snowflake) Experience in tools such as GitHub Actions, Terraform, containers Proven track record in leading data engineering teams, mentoring staff, and promoting a culture of learning and teaching. Demonstrated ability to take risks when seeking novel solutions to complex problems and to persist in the face of You Will Use & Must Be Well-versed With : Python for data pipelining and automation Airbyte and Airflow for ETL purposes. GCP or AWS platforms utilizing tools like Terraform, Container services (GKE/EKS), Cloud Functions / Lambda, BigQuery/Snowflake dbt for data modeling. PowerBI for data visualization and consumer-facing dashboard (ref:hirist.tech) Show more Show less

Career Area: Technology, Digital and Data Job Description: Your Work Shapes the World at Caterpillar Inc. When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it. Role Definition Performs implementation, regular problem solving, maintenance and support for a agile software development. Responsibilities Designing, modifying, developing, writing and implementing software programming applications for target system using agile methods. Acquiring client requirements; resolving workflow problems through automation optimization. Writing source codes for new applications, and/or generating and enhancing code samples for existing applications. Utilizing automated testing tools to perform the testing and maintenance. Skill Descriptors Decision Making and Critical Thinking: Knowledge of the decision-making process and associated tools and techniques; ability to accurately analyze situations and reach productive decisions based on informed judgment. Level Working Knowledge: Applies an assigned technique for critical thinking in a decision-making process. Identifies, obtains, and organizes relevant data and ideas. Participates in documenting data, ideas, players, stakeholders, and processes. Recognizes, clarifies, and prioritizes concerns. Assists in assessing risks, benefits and consideration of alternatives. Effective Communications: Understanding of effective communication concepts, tools and techniques; ability to effectively transmit, receive, and accurately interpret ideas, information, and needs through the application of appropriate communication behaviors. Level Working Knowledge: Delivers helpful feedback that focuses on behaviors without offending the recipient. Listens to feedback without defensiveness and uses it for own communication effectiveness. Makes oral presentations and writes reports needed for own work. Avoids technical jargon when inappropriate. Looks for and considers non-verbal cues from individuals and groups. Software Development: Knowledge of software development tools and activities; ability to produce software products or systems in line with product requirements. Level Extensive Experience: Conducts walkthroughs and monitors effectiveness and quality of the development activities. Elaborates on multiple-development toolkits for traditional and web-based software. Has participated in development of multiple or large software products. Contrasts advantages and drawbacks of different development languages and tools. Estimates and monitors development costs based on functional and technical requirements. Provides consulting on both selection and utilization of developers' workbench tools. Software Development Life Cycle: Knowledge of software development life cycle; ability to use a structured methodology for delivering and managing new or enhanced software products to the marketplace. Level Working Knowledge: Describes similarities and differences of life cycle for new product development vs. new release. Identifies common issues, problems, and considerations for each phase of the life cycle. Works with a formal life cycle methodology. Explains phases, activities, dependencies, deliverables, and key decision points. Interprets product development plans and functional documentation. Software Integration Engineering: Knowledge of software integration processes and functions; ability to design, develop and maintain interfaces and linkage to alternative platforms and software packages. Level Working Knowledge: Has experience with designing data exchange interfaces to and from software product. Describes tools and techniques for extraction, transformation and loading of electronic data. Cites examples of common linkage requirements for software products and vendors. Works with integrating software into the customer or partner framework and infrastructure. Participates in the development of technology interfaces and bridges. Software Product Design/Architecture: Knowledge of software product design; ability to convert market requirements into the software product design. Level Extensive Experience: Demonstrates experience with the architecture and design of major or multiple products. Describes major software architecture alternatives and considerations. Explains design considerations for commercial database systems, operating systems and web. Displays experience in estimating the cost of a specific design of a proposed product. Facilitates design reviews and walkthroughs. Analyzes benefits and drawbacks of specific software designs and architecture. Software Product Technical Knowledge: Knowledge of technical aspects of a software products; ability to design, configure and integrate technical aspects of software products. Level Working Knowledge: Maintains and utilizes data related to install base configurations and environments. Solicits customer feedback; reports and monitors bugs and implementation issues. Participates in defining and conducting technical acceptance tests. Participates in creating technical requirements for software development and deployment. Explains basic environment and product configuration options. Software Product Testing: Knowledge of software product testing; ability to design, plan, and execute testing strategies and tactics to ensure software product quality and adherence to stated requirements. Level Working Knowledge: Participates in test readiness reviews, functional, volume, and load testing. Describes key features and aspects of a specific testing discipline or methodology. Tests software components for compliance with functional requirements and design specifications. Explains procedures for documenting test activities and results (e.g. errors, non-conformance, etc.) Conducts functional and performance testing on aspects of assigned products. Responsibilities: Top Candidates will have : Data Pipeline Development: Design, develop, and maintain scalable and efficient ETL/ELT pipelines using Python and AWS services (e.g., Lambda, Glue, S3, EC2, Step Functions). Data Warehousing: Architect, implement, and optimize data models and queries within Snowflake, ensuring optimal performance and scalability. Cloud Infrastructure: Manage and maintain data infrastructure on AWS, including provisioning, monitoring, and troubleshooting. Data Quality and Governance: Implement data quality checks and monitoring processes to ensure data integrity and reliability. Performance Optimization: Identify and resolve performance bottlenecks in data pipelines and queries. Collaboration: Work closely with data scientists, analysts, and other engineers to understand data requirements and deliver effective solutions. Automation: Automate data engineering tasks and processes to improve efficiency and reduce manual effort. Documentation: Create and maintain comprehensive documentation for data pipelines, infrastructure, and processes. Mentorship: Mentor junior data engineers and contribute to the team's knowledge sharing and best practices. Security: Implement and maintain data security best practices. Required Skills And Experience: Expertise in Python programming for data processing and automation. Strong proficiency in SQL for data manipulation and analysis. Extensive experience with AWS cloud services, particularly those related to data engineering (e.g., S3, Glue, Lambda, EC2, IAM, Step Functions, CloudWatch). Proven experience with Snowflake data warehousing. Experience designing and implementing ETL/ELT pipelines. Strong understanding of data modeling concepts and best practices. Experience with version control systems (e.g., Git). Excellent problem-solving and analytical skills. Strong communication and collaboration skills. Experience with data orchestration tools like Airflow or similar. Preferred Skills: Experience with data streaming technologies (e.g., Kafka, Kinesis). Experience with infrastructure as code (IaC) tools (e.g., Terraform, CloudFormation). Experience with building data lakes. Experience with CI/CD pipelines in AZDO. This Job Description is intended as a general guide to the job duties for this position and is intended for the purpose of establishing the specific salary grade. It is not designed to contain or be interpreted as an exhaustive summary of all responsibilities, duties and effort required of employees assigned to this job. At the discretion of management, this description may be changed at any time to address the evolving needs of the organization. It is expressly not intended to be a comprehensive list of “essential job functions” as that term is defined by the Americans with Disabilities Act. Posting Dates: June 10, 2025 - June 23, 2025 Caterpillar is an Equal Opportunity Employer. Not ready to apply? Join our Talent Community. Show more Show less

Job Description Mactores is seeking an AWS Data Engineer (Senior) to join our team. The ideal candidate will have extensive experience in PySpark and SQL and have worked with data pipelines using Amazon EMR or Amazon Glue. The candidate must also have experience in data modeling and end-user querying using Amazon Redshift or Snowflake, Amazon Athena, Presto, and orchestration experience using Airflow. Responsibilities Develop and maintain data pipelines using Amazon EMR or Amazon Glue. Create data models and end-user querying using Amazon Redshift or Snowflake, Amazon Athena, and Presto. Build and maintain the orchestration of data pipelines using Airflow. Collaborate with other teams to understand their data needs and help design solutions. Troubleshoot and optimize data pipelines and data models. Write and maintain PySpark and SQL scripts to extract, transform, and load data. Document and communicate technical solutions to both technical and non-technical audiences. Stay up-to-date with new AWS data technologies and evaluate their impact on our existing systems. Requirements Bachelor's degree in Computer Science, Engineering, or a related field. 3+ years of experience working with PySpark and SQL. 2+ years of experience building and maintaining data pipelines using Amazon EMR or Amazon Glue. 2+ years of experience with data modeling and end-user querying using Amazon Redshift or Snowflake, Amazon Athena, and Presto. 1+ years of experience building and maintaining the orchestration of data pipelines using Airflow. Strong problem-solving and troubleshooting skills. Excellent communication and collaboration skills. Ability to work independently and within a team environment. You Are Preferred If You Have AWS Data Analytics Specialty Certification. Experience with Agile development methodology. (ref:hirist.tech) Show more Show less

Mactores is a trusted leader among businesses in providing modern data platform solutions. Since 2008, Mactores have been enabling businesses to accelerate their value through automation by providing End-to-End Data Solutions that are automated, agile, and secure. We collaborate with customers to strategize, navigate, and accelerate an ideal path forward with a digital transformation via assessments, migration, or modernization. Mactores is seeking an AWS Data Engineer (Senior) to join our team. The ideal candidate will have extensive experience in PySpark and SQL, and have worked with data pipelines using Amazon EMR or Amazon Glue. The candidate must also have experience in data modeling and end-user querying using Amazon Redshift or Snowflake, Amazon Athena, Presto, and orchestration experience using Airflow. What you will do ? Develop and maintain data pipelines using Amazon EMR or Amazon Glue. Create data models and end-user querying using Amazon Redshift or Snowflake, Amazon Athena, and Presto. Build and maintain the orchestration of data pipelines using Airflow. Collaborate with other teams to understand their data needs and help design solutions. Troubleshoot and optimize data pipelines and data models. Write and maintain PySpark and SQL scripts to extract, transform, and load data. Document and communicate technical solutions to both technical and non-technical audiences. Stay up-to-date with new AWS data technologies and evaluate their impact on our existing systems. What are we looking for? Bachelor's degree in Computer Science, Engineering, or a related field. 3+ years of experience working with PySpark and SQL. 2+ years of experience building and maintaining data pipelines using Amazon EMR or Amazon Glue. 2+ years of experience with data modeling and end-user querying using Amazon Redshift or Snowflake, Amazon Athena, and Presto. 1+ years of experience building and maintaining the orchestration of data pipelines using Airflow. Strong problem-solving and troubleshooting skills. Excellent communication and collaboration skills. Ability to work independently and within a team environment. You Are Preferred If You Have AWS Data Analytics Specialty Certification Experience with Agile development methodology Life at Mactores We care about creating a culture that makes a real difference in the lives of every Mactorian. Our 10 Core Leadership Principles that honor Decision-making, Leadership, Collaboration, and Curiosity drive how we work. Be one step ahead Deliver the best Be bold Pay attention to the detail Enjoy the challenge Be curious and take action Take leadership Own it Deliver value Be collaborative We would like you to read more details about the work culture on https://mactores.com/careers The Path to Joining the Mactores Team At Mactores, our recruitment process is structured around three distinct stages: Pre-Employment Assessment: You will be invited to participate in a series of pre-employment evaluations to assess your technical proficiency and suitability for the role. Managerial Interview: The hiring manager will engage with you in multiple discussions, lasting anywhere from 30 minutes to an hour, to assess your technical skills, hands-on experience, leadership potential, and communication abilities. HR Discussion: During this 30-minute session, you'll have the opportunity to discuss the offer and next steps with a member of the HR team. (ref:hirist.tech) Show more Show less

Job Title : Data : Bangalore : 3+ : the Opportunity : We Are Urgently Looking For Experienced Data Engineers To Join Our Team At Hexamobile, Bangalore. Ideal Candidates Will Have a Strong Background In Python, PySpark, And ETL Processes, With Azure Cloud Experience Being a Strong Design, develop, and maintain scalable and efficient data pipelines using Python and PySpark. Build and optimize ETL (Extract, Transform, Load) processes to ingest, clean, transform, and load data from various sources into data warehouses and data lakes. Work with large and complex datasets, ensuring data quality, integrity, and reliability. Collaborate closely with data scientists, analysts, and other stakeholders to understand their data requirements and provide them with clean and well-structured data. Monitor and troubleshoot data pipelines, identifying and resolving issues to ensure continuous data flow. Implement data quality checks and validation processes to maintain high data accuracy. Develop and maintain comprehensive documentation for data pipelines, ETL processes, and data models. Optimize data systems and pipelines for performance, scalability, and cost-efficiency. Implement data security and governance policies and procedures. Stay up-to-date with the latest advancements in data engineering technologies and best practices. Work in an agile environment, participating in sprint planning, daily stand-ups, and code reviews. Contribute to the design and architecture of our data Skills : Python : Strong proficiency in Python programming, including experience with data manipulation libraries (e.g., Pandas, NumPy). PySpark : Extensive hands-on experience with Apache Spark using PySpark for large-scale data processing and distributed computing. ETL Processes : Deep understanding of ETL concepts, methodologies, and best practices. Proven experience in designing, developing, and implementing ETL pipelines. SQ L: Solid understanding of SQL and experience in querying, manipulating, and transforming data in relational databases. Understanding of Databases : Strong understanding of various database systems, including relational databases (e.g., PostgreSQL, MySQL, SQL Server) and potentially NoSQL databases. Version Control : Experience with version control systems, particularly Git, and platforms like GitHub or GitLab (i.e., working with branches and pull Preferred Skills : Azure Cloud Experience: Hands-on experience with Microsoft Azure cloud services, particularly data-related services such as : Azure Data Factory Azure Databricks Azure Blob Storage Azure SQL Database Azure Data Lake Storage Experience with data warehousing concepts and : Bachelor's degree in Computer Science, Engineering, or a related field. Minimum of 3 years of professional experience as a Data Engineer. Proven experience in building and maintaining data pipelines using Python and PySpark. Strong analytical and problem-solving skills. Good verbal and written communication skills. Ability to work effectively both independently and as part of a team. Must be available to join Points : Experience with other big data technologies (Hadoop, Hive, Kafka, Apache Airflow). Knowledge of data governance and data quality frameworks. Experience with CI/CD pipelines for data engineering workflows. Familiarity with data visualization tools (Power BI, Tableau). Experience with other cloud platforms (AWS, GCP). (ref:hirist.tech) Show more Show less

GCP Data Engineer We are looking for a GCP Data Engineer to design, develop, and maintain scalable data pipelines and cloud-based data platforms. You will work on building and optimizing data workflows, implementing robust data solutions using Google Cloud Platform (GCP) technologies, and collaborating closely with cross-functional teams to deliver high-impact, data-driven insights. This role requires a deep understanding of data architecture, GCP ecosystem, ETL/ELT processes, and the ability to lead, mentor, and execute with precision. Key Responsibilities Design, build, and maintain robust data extraction, transformation, and loading (ETL/ELT) pipelines across both on-premises and cloud platforms. Develop and support data products, pipelines, and analytical platforms leveraging GCP services. Perform application impact assessments, requirement reviews, and provide accurate work estimates. Create test strategies and implement site reliability engineering (SRE) measures for data systems. Participate in agile development sprints and contribute to solution design reviews. Mentor and guide junior Data Engineers on best practices and design patterns. Lead root cause analysis and resolution of critical data operations and post-implementation issues. Conduct technical data stewardship activities, including metadata management, data security, and privacy-by-design principles. Use Python and GCP technologies to automate data workflows and transformations. Work with SQL for data modeling, transformations, and analytical queries. Automate job scheduling and orchestration using Control-M, Apache Airflow, or Prefect. Write Unix shell scripts to support automation and monitoring of data operations. Support BI/analytics teams with structured and well-modeled data. Use Infrastructure as Code (IaC) tools like Terraform, Ansible, or Puppet for automated deployments and configuration management. Required Skills & Technologies Strong experience with Python, SQL, and Unix/Linux scripting. Proficient in GCP Data Services. Experience in designing and managing ETL/ELT pipelines across hybrid environments. Working knowledge of orchestration tools: Apache Airflow, Control-M, or Prefect. Understanding of modern data warehousing and cloud-based analytics architecture. Familiarity with Infrastructure-as-Code using Terraform, Puppet, or Ansible. Strong debugging and problem-solving abilities in complex data environments. Ability to work in Agile teams and deliver in short sprint cycles. Qualifications Bachelors degree in Computer Science, Software Engineering, Data Science, Mathematics, or related field. 4+ years of hands-on experience in data engineering. 2+ years of experience in data architecture and solution design. GCP Certified Data Engineer certification is preferred. Excellent communication skills and the ability to collaborate with cross-functional teams. (ref:hirist.tech) Show more Show less

Key Responsibilities Design, develop, and maintain scalable data pipelines and architectures using AWS services. Implement ETL/ELT processes using AWS Glue, Lambda, and Step Functions. Work with structured and unstructured data across S3, Redshift, and other AWS data services. Develop data integration workflows to collect, process, and store data efficiently. Optimize performance and cost of data pipelines. Monitor and troubleshoot data pipeline failures using CloudWatch and related tools. Collaborate with data analysts, data scientists, and other stakeholders to ensure data availability and quality. Apply best practices for security and governance of data assets on Skills : 3+ years of experience in Python, SQL, and PySpark. 2+ years of experience with AWS services such as : AWS Glue AWS Lambda Amazon S3 Amazon EC2 Amazon Redshift CloudWatch Experience in building and maintaining ETL pipelines. Knowledge of data lake and data warehouse architecture. Familiarity with DevOps tools and CI/CD pipelines is a plus. Good understanding of data governance and security best practices on AWS. Preferred Qualifications AWS Certified Data Analytics Specialty or AWS Certified Solutions Architect. Experience with other cloud platforms (Azure, GCP) is a plus. Exposure to tools like Apache Airflow, Kafka, or Snowflake is an added advantage. (ref:hirist.tech) Show more Show less

Key Responsibilities Design and develop robust ETL/ELT pipelines using Python and AWS Glue / Lambda Work with AWS services such as S3, Athena, Redshift, Glue, Step Functions, and CloudWatch Build and maintain data integration processes between internal and external data sources Optimize data pipelines for performance, scalability, and reliability Implement data quality checks and monitoring Collaborate with data analysts, engineers, and product teams to meet data requirements Maintain proper documentation and ensure best practices in data engineering Work with structured and semi-structured data formats (JSON, Parquet, Skills : 46 years of experience as a Data Engineer Strong programming skills in Python (Pandas, Boto3, PySpark) Proficient in SQL and performance tuning Hands-on experience with AWS services : S3, Glue, Lambda, Athena, Redshift, Step Functions, CloudWatch Experience working with Databricks or EMR is a plus Experience in data lake and data warehouse concepts Familiar with version control systems like Git Knowledge of CI/CD pipelines and workflow tools (Airflow is a plus) (ref:hirist.tech) Show more Show less

Key Responsibilities Design, develop, and optimize large-scale data pipelines using PySpark and Apache Spark. Build scalable and robust ETL workflows leveraging AWS services such as EMR, S3, Lambda, and Glue. Collaborate with data scientists, analysts, and other engineers to gather requirements and deliver clean, well-structured data solutions. Integrate data from various sources, ensuring high data quality, consistency, and reliability. Manage and schedule workflows using Apache Airflow. Work on ML model deployment pipelines using tools like SageMaker and Anaconda. Write efficient and optimized SQL queries for data processing and validation. Develop and maintain technical documentation for data pipelines and architecture. Participate in Agile ceremonies, sprint planning, and code reviews. Troubleshoot and resolve issues in production environments with minimal supervision. Required Skills And Qualifications Bachelor's or Masters degree in Computer Science, Engineering, or a related field. 68 years of experience in data engineering with a strong focus on : Python PySpark SQL AWS (EMR, EC2, S3, Lambda, Glue) Experience in developing and orchestrating pipelines using Apache Airflow. Familiarity with SageMaker for ML deployment and Anaconda for environment management. Proficiency in working with large datasets and optimizing Spark jobs. Experience in building data lakes and data warehouses on AWS. Strong understanding of data governance, data quality, and data lineage. Excellent documentation and communication skills. Comfortable working in a fast-paced Agile environment. Experience with Kafka or other real-time streaming platforms. Familiarity with DevOps practices and tools (e.g., Terraform, CloudFormation). Exposure to NoSQL databases such as DynamoDB or MongoDB. Knowledge of data security and compliance standards (GDPR, HIPAA). Work with cutting-edge technologies in a collaborative and innovative environment. Opportunity to influence large-scale data infrastructure. Competitive salary, benefits, and professional development support. Be part of a growing team solving real-world data challenges. (ref:hirist.tech) Show more Show less

Urgent Hiring _ Azure Data Engineer with a leading Management Consulting Company @ Bangalore Location. Strong expertise in Databricks & Pyspark while dealing with batch processing or live (streaming) data sources. 4+ relevant years of experience in Databricks & Pyspark/Scala 7+ total years of experience Good in data modelling and designing. Ctc- Hike Shall be considered on Current/Last Drawn Pay Apply - rohita.robert@adecco.com Has worked on real data challenges and handled high volume, velocity, and variety of data. Excellent analytical & problem-solving skills, willingness to take ownership and resolve technical challenges. Contributes to community building initiatives like CoE, CoP. Mandatory skills: Azure - Master ELT - Skill Data Modeling - Skill Data Integration & Ingestion - Skill Data Manipulation and Processing - Skill GITHUB, Action, Azure DevOps - Skill Data factory, Databricks, SQL DB, Synapse, Stream Analytics, Glue, Airflow, Kinesis, Redshift, SonarQube, PyTest - Skill

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 Design, develop, and operate high scale applications across the full engineering stack Design, develop, test, deploy, maintain, and improve software. Apply modern software development practices (serverless computing, microservices architecture, CI/CD, infrastructure-as-code, etc.) Work across teams to integrate our systems with existing internal systems, Data Fabric, CSA Toolset. Participate in technology roadmap and architecture discussions to turn business requirements and vision into reality. Participate in a tight-knit, globally distributed engineering team. Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on network, or service operations and quality. Manage sole project priorities, deadlines, and deliverables. Research, create, and develop software applications to extend and improve on Equifax Solutions Collaborate on scalability issues involving access to data and information. Actively participate in Sprint planning, Sprint Retrospectives, and other team activity What Experience You Need Bachelor's degree or equivalent experience 5+ years of software engineering experience 5+ years experience writing, debugging, and troubleshooting code in mainstream Java, SpringBoot, TypeScript/JavaScript, HTML, CSS 5+ years experience with Cloud technology: GCP, AWS, or Azure 5+ years experience designing and developing cloud-native solutions 5+ years experience designing and developing microservices using Java, SpringBoot, GCP SDKs, GKE/Kubernetes 5+ 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. 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 . Agile environments (e.g. Scrum, XP) Relational databases Atlassian tooling (e.g. JIRA, Confluence, and Github) Developing with modern JDK (v1.7+) 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

Were Hiring! | Senior Data Engineer (Remote) Location: Remote | Shift: US - CST Time | Department: Data Engineering Are you a data powerhouse who thrives on solving complex data challenges? Do you love working with Python, AWS, and cutting-edge data tools? If yes, Atidiv wants YOU! Were looking for a Senior Data Engineer to build and scale data pipelines, transform how we manage data lakes and warehouses, and power real-time data experiences across our products. What Youll Do: Architect and develop robust, scalable data pipelines using Python & PySpark Drive real-time & batch data ingestion from diverse data sources Build and manage data lakes and data warehouses using AWS (S3, Glue, Redshift, EMR, Lambda, Kinesis) Write high-performance SQL queries and optimize ETL/ELT jobs Collaborate with data scientists, analysts, and engineers to ensure high data quality and availability Implement monitoring, logging & alerting for workflows Ensure top-tier data security, compliance & governance What We’re Looking For: 5+ years of hands-on experience in Data Engineering Strong skills in Python, DBT, SQL , and working with Snowflake Proven experience with Airflow, Kafka/Kinesis , and AWS ecosystem Deep understanding of CI/CD practices Passion for clean code, automation , and scalable systems Why Join Atidiv? 100% Remote | Flexible Work Culture Opportunity to work with cutting-edge technologies Collaborative, supportive team that values innovation and ownership Work on high-impact, global projects Ready to transform data into impact? Send your resume to: nitish.pati@atidiv.com

Who You’ll Work With A data engineer will work in the Data and Artificial Intelligence organisation of Nike and will focus on building highly complex and performant data pipelines that'll drive Nike's data driven strategies for the future of sports. Who We Are Looking For In this role, we are looking for self-driven individuals who have deep technical knowledge in the big data domain. This role requires the individual to be an excellent problem solver who'll design and implement complex data pipelines which solve business problems of Nike. The core competencies required for this role include - Bachelor’s degree in computer science engineering 2+ years of hands-on experience in data engineering field In depth big data tech stack knowledge Expertise in pyspark and SQL Expertise in databricks, snowflake, airflow Excellent written and verbal communication skills What You’ll Work On As a data engineer you'll be a key pillar of the data engineering team. You will collaborate closely with other engineers to deliver key changes to data pipelines that drive Nike's data strategy On a day-to-day basis, you'll focus on - Building, enhancing, and troubleshooting complex data pipelines Collaborating with product managers, engineers, analysts to build, enhance and troubleshoot data pipelines Collaborate with senior, lead and principal engineers to define and implement quality standards across data pipelines Contribute towards the design and architecture of data pipelines Implement data quality and reliability measures across data pipelines Show more Show less

Who You’ll Work With This role is part of the Nike’s Content Technology team within Consumer Product and Innovation (CP&I) organization, working very closely with the globally distributed Engineering and Product teams. This role will roll up to the Director Software Engineering based out of Nike India Tech Centre. Who We Are Looking For We are looking for experienced Technology focused and hands on Lead Engineer to join our team in Bengaluru, India. As a Senior Data Engineer, you will play a key role in ensuring that our data products are robust and capable of supporting our Data Engineering and Business Intelligence initiatives. A data engineer with 2+ years of experience in data engineering. Proficient in SQL, Python, PySpark, and Apache Airflow (or similar workflow management tools). Hands-on experience with Databricks, Snowflake, and cloud platforms (AWS/GCP/Azure). Good understanding of Spark, Delta Lake, Medallion architecture, and ETL/ELT processes. Solid data modeling and data profiling skills. Familiarity with Agile methodologies (Scrum/Kanban). Awareness of DevOps practices in data engineering (automated testing, security administration, workflow orchestration) Exposure to Kafka or real-time data processing Strong communication and collaboration skills. Preferred: familiarity with Tableau or similar BI tools exposure to GenAI/ML pipelines Nice to have: Databricks certifications for data engineer, developer, or Apache Spark. What You’ll Work On Build and maintain ETL/ELT pipelines and reusable data components. Collaborate with peers and stakeholders to gather data requirements. Participate in code reviews and contribute to quality improvements. Monitor and troubleshoot data pipelines for performance and reliability. Support CI/CD practices in data engineering workflows. Show more Show less

We are looking for a hands-on Data Engineer who is passionate about solving business problems through innovation and engineering practices. As a Data Engineer, the candidate will leverage deep technical knowledge and will apply knowledge of data architecture standards, data warehousing, data structures, and business intelligence to drive the creation of high-quality data products for data driven decision making. Required Qualifications 3-6 Years Experience of implementing data-intensive solutions using agile methodologies. Code contributing member of Agile teams, working to deliver sprint goals. Write clean, efficient, and maintainable code that meets the highest standards of quality. Very strong in coding Python/Pyspark, UNIX shell scripting Experience in cloud native technologies and patterns Ability to automate and streamline the build, test and deployment of data pipelines T echnical Skills (Must Have) ETL: Hands on experience of building data pipelines. Proficiency in data integration platforms such as Apache Spark Experienced in writing Pyspark code to handle large data set ,perform data transformation , familiarity with Pyspark integration with other Apache Spark component ,such as Spark SQL , Understanding of Pyspark optimization techniques Strong proficiency in working with relational databases and using SQL for data querying, transformation, and manipulation. Big Data: Exposure to ‘big data’ platforms such as Hadoop, Hive or Iceberg for data storage and processing Data Warehousing & Database Management: Understanding of Data Warehousing concepts, Relational (Oracle, MSSQL, MySQL) and NoSQL (MongoDB, DynamoDB) database design Data Modeling & Design: Good exposure to data modeling techniques; design, optimization and maintenance of data models and data structures Languages: Proficient in one or more programming languages commonly used in data engineering such as Python, PySpark, UNIX Shell scripting DevOps: Exposure to concepts and enablers - CI/CD platforms, bitbucket/Github, JIRA, Jenkins, Tekton, Harness Technical Skills (Valuable) Data Quality & Controls: Exposure to data validation, cleansing, enrichment and data controls, framework libraries like Deequ Federated Query: Starburst, Trino Containerization: Fair understanding of containerization platforms like Docker, Kubernetes, Openshift File Formats: Exposure in working on File/Table Formats such as Avro, Parquet, Iceberg, Delta Schedulers: Basics of Job scheduler like Autosys, Airflow Cloud: Experience in cloud native technologies and patterns (AWS, Google Cloud) Nice to have: Java, for REST API development Other skills : Strong project management and organizational skills. Excellent problem-solving, communication, and organizational skills. Proven ability to work independently and with a team. Experience in managing and implementing successful projects Ability to adjust priorities quickly as circumstances dictate Consistently demonstrates clear and concise written and verbal communication ------------------------------------------------------ Job Family Group: Technology ------------------------------------------------------ Job Family: Applications Development ------------------------------------------------------ Time Type: Full time ------------------------------------------------------ Most Relevant Skills Please see the requirements listed above. ------------------------------------------------------ Other Relevant Skills For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------ Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi. View Citi’s EEO Policy Statement and the Know Your Rights poster. Show more Show less