267 Data Pipelines Jobs - Page 10

We are looking for a highly experienced Lead Data Engineer / Data Architect to lead the design, development, and implementation of scalable data pipelines, data Lakehouse, and data warehousing solutions. The ideal candidate will provide technical leadership to a team of data engineers, drive architectural decisions, and ensure best practices in data engineering. This role is critical in enabling data-driven decision-making and modernizing our data infrastructure. Key Responsibilities: Act as a technical leader responsible for guiding the design, development, and implementation of data pipelines, data Lakehouse, and data warehousing solutions. Lead a team of data engineers, ensuring adherence to best practices and standards. Drive the successful delivery of high-quality, scalable, and reliable data solutions. Play a key role in shaping data architecture, adopting modern data technologies, and enabling data-driven decision-making across the team. Provide technical vision, guidance, and mentorship to the team. Lead technical design discussions, perform code reviews, and contribute to architectural decisions.

We are hiring a Senior Data Engineer for a 6-month remote contract position. The ideal candidate is highly skilled in building scalable data pipelines and working within the Azure cloud ecosystem, especially Databricks, ADF, and PySpark. You'll work closely with cross-functional teams to deliver enterprise-level data engineering solutions. #KeyResponsibilities Build scalable ETL pipelines and implement robust data solutions in Azure. Manage and orchestrate workflows using ADF, Databricks, ADLS Gen2, and Key Vaults. Design and maintain secure and efficient data lake architecture. Work with stakeholders to gather data requirements and translate them into technical specs. Implement CI/CD pipelines for seamless data deployment using Azure DevOps. Monitor data quality, performance bottlenecks, and scalability issues. Write clean, organized, reusable PySpark code in an Agile environment. Document pipelines, architectures, and best practices for reuse. #MustHaveSkills Experience: 6+ years in Data Engineering Tech Stack: SQL, Python, PySpark, Spark, Azure Databricks, ADF, ADLS Gen2, Azure DevOps, Key Vaults Core Expertise: Data Warehousing, ETL, Data Pipelines, Data Modelling, Data Governance Agile, SDLC, Containerization (Docker), Clean coding practices #GoodToHaveSkills Event Hubs, Logic Apps Power BI Strong logic building and competitive programming background #ContractDetails Role: Senior Data Engineer Locations : Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, India Duration: 6 Months Email to Apply: navaneeta@suzva.com Contact: 9032956160

Roles & Responsibilities Lead and manage the enterprise data operations team responsible for data ingestion, processing, validation, quality control, and publishing Define and implement SOPs for data lifecycle management ensuring data accuracy, completeness, and integrity Oversee and improve daily operational workflows: scheduling, monitoring, troubleshooting data jobs across cloud and on-prem environments Establish and track key data operations metrics (SLAs, throughput, latency, data quality, incident resolution) and drive continuous improvement Partner with data engineering and platform teams to optimize pipelines, support integrations, and ensure scalability and resilience Collaborate with governance, compliance, and security teams to maintain regulatory compliance, data privacy, and access controls Serve as the primary escalation point for data incidents and outages, ensuring rapid response and root cause analysis Build strong relationships with business and analytics teams to understand data needs and prioritize operational goals Drive adoption of best practices for documentation, metadata, lineage, and change management Mentor and develop a high-performing team of data operations analysts and leads Must-Have Skills Experience managing data engineering teams in biotech/pharma domains Expertise in designing and maintaining ETL data pipelines and analytics solutions Hands-on experience with cloud platforms (AWS preferred) for scalable, cost-effective data solutions Experience managing data workflows on AWS, Azure, or GCP Strong problem-solving and analytical skills for complex data flow issues Proficiency in SQL, Python, or scripting for process monitoring and automation Collaboration experience across data engineering, analytics, IT ops, and business teams in matrix organizations Familiarity with data governance, metadata management, access control, and compliance frameworks (GDPR, HIPAA, SOX) Excellent leadership, communication, and stakeholder management skills Knowledge of full stack development, DataOps automation, logging frameworks, and pipeline orchestration tools Good-to-Have Skills Data Engineering management experience in Biotech/Life Sciences/Pharma Experience with graph databases (Stardog, Marklogic, Neo4J, Allegrograph) Education & Professional Certifications Doctorate degree with 3-5+ years experience OR Master's degree with 6-8+ years experience OR Bachelor's degree with 10-12+ years experience in Computer Science, IT, or related field AWS Certified Data Engineer (preferred) Databricks Certificate (preferred) Scaled Agile SAFe certification (preferred) Soft Skills Excellent analytical and troubleshooting skills Strong verbal and written communication Ability to work effectively with global, virtual teams High initiative and self-motivation Ability to manage multiple priorities successfully Team-oriented mindset focused on achieving goals Strong presentation and public speaking skills

Req ID: 323226 NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now. We are currently seeking a Digital Solution Architect Sr. Advisor to join our team in Bengaluru, India, Karn?taka (IN-KA), India (IN). Key Responsibilities: Design data platform architectures (data lakes, lakehouses, DWH) using modern cloud-native tools (e.g., Databricks, Snowflake, BigQuery, Synapse, Redshift). Architect data ingestion, transformation, and consumption pipelines using batch and streaming methods. Enable real-time analytics and machine learning through scalable and modular data frameworks. Define data governance models, metadata management, lineage tracking, and access controls. Collaborate with AI/ML, application, and business teams to identify high-impact use cases and optimize data usage. Lead modernization initiatives from legacy data warehouses to cloud-native and distributed architectures. Enforce data quality and observability practices for mission-critical workloads. Required Skills: 10+ years in data architecture, with strong grounding in modern data platforms and pipelines. Deep knowledge of SQL/NoSQL, Spark, Delta Lake, Kafka, ETL/ELT frameworks. Hands-on experience with cloud data platforms (AWS, Azure, GCP). Understanding of data privacy, security, lineage, and compliance (GDPR, HIPAA, etc.). Experience implementing data mesh/data fabric concepts is a plus. Expertise in technical solutions writing and presenting using tools such as Word, PowerPoint, Excel, Visio etc. High level of executive presence to be able to articulate the solutions to CXO level executives. Preferred Qualifications: Certifications in Snowflake, Databricks, or cloud-native data platforms. Exposure to AI/ML data pipelines, MLOps, and real-time data applications. Familiarity with data visualization and BI tools (Power BI, Tableau, Looker, etc.). About NTT DATA NTT DATA is a $30 billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long term success. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure and connectivity. We are one of the leading providers of digital and AI infrastructure in the world. NTT DATA is a part of NTT Group, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Visit us at NTT DATA endeavors to make accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at . This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click . If you'd like more information on your EEO rights under the law, please click . For Pay Transparency information, please click.

Introduction In this role, youll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology In this role, youll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology. Your role and responsibilities Work with broader team to build, analyze and improve the AI solutions. You will also work with our software developers in consuming different enterprise applications Required education Bachelors Degree Preferred education Masters Degree Required technical and professional expertise Resource should have 5-7 years of experience. Sound knowledge of Python and should know how to use the ML related services. Proficient in Python with focus on Data Analytics Packages. Strategy Analyse large, complex data sets and provide actionable insights to inform business decisions. Strategy Design and implementing data models that help in identifying patterns and trends. Collaboration Work with data engineers to optimize and maintain data pipelines. Perform quantitative analyses that translate data into actionable insights and provide analytical, data-driven decision-making. Identify and recommend process improvements to enhance the efficiency of the data platform. Develop and maintain data models, algorithms, and statistical models Preferred technical and professional experience Experience with conversation analytics. Experience with cloud technologies Experience with data exploration tools such as Tableu

Introduction In this role, youll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology. In this role, youll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology. Your role and responsibilities Work with broader team to build, analyze and improve the AI solutions. You will also work with our software developers in consuming different enterprise applications Required education Bachelors Degree Preferred education Masters Degree Required technical and professional expertise Resource should have 5-7 years of experience. Sound knowledge of Python and should know how to use the ML related services. Proficient in Python with focus on Data Analytics Packages. Strategy Analyse large, complex data sets and provide actionable insights to inform business decisions. Strategy Design and implementing data models that help in identifying patterns and trends. Collaboration Work with data engineers to optimize and maintain data pipelines. Perform quantitative analyses that translate data into actionable insights and provide analytical, data-driven decision-making. Identify and recommend process improvements to enhance the efficiency of the data platform. Develop and maintain data models, algorithms, and statistical models Preferred technical and professional experience Experience with conversation analytics. Experience with cloud technologies Experience with data exploration tools such as Tableu

Job Summary: We are seeking an experienced Snowflake Data Engineer to design, develop, and optimize data pipelines and data architecture using the Snowflake cloud data platform. The ideal candidate will have a strong background in data warehousing, ETL/ELT processes, and cloud platforms, with a focus on creating scalable and high-performance solutions for data integration and analytics. --- Key Responsibilities: * Design and implement data ingestion, transformation, and loading processes (ETL/ELT) using Snowflake. * Build and maintain scalable data pipelines using tools such as dbt, Apache Airflow, or similar orchestration tools. * Optimize data storage and query performance in Snowflake using best practices in clustering, partitioning, and caching. * Develop and maintain data models (dimensional/star schema) to support business intelligence and analytics initiatives. * Collaborate with data analysts, scientists, and business stakeholders to gather data requirements and translate them into technical solutions. * Manage Snowflake environments including security (roles, users, privileges), performance tuning, and resource monitoring. * Integrate data from multiple sources including cloud storage (AWS S3, Azure Blob), APIs, third-party platforms, and streaming data. * Ensure data quality, reliability, and governance through testing and validation strategies. * Document data flows, definitions, processes, and architecture. --- Required Skills and Qualifications: * 3+ years of experience as a Data Engineer or in a similar role working with large-scale data systems. * 2+ years of hands-on experience with Snowflake including SnowSQL, Snowpipe, Streams, Tasks, and Time Travel. * Strong experience in SQL and performance tuning for complex queries and large datasets. * Proficiency with ETL/ELT tools such as dbt, Apache NiFi, Talend, Informatica, or custom scripts. * Solid understanding of data modeling concepts (star schema, snowflake schema, normalization, etc.). * Experience with cloud platforms (AWS, Azure, or GCP), particularly using services like S3, Redshift, Lambda, Azure Data Factory, etc. * Familiarity with Python or Java or Scala for data manipulation and pipeline development. * Experience with CI/CD processes and tools like Git, Jenkins, or Azure DevOps. * Knowledge of data governance, data quality, and data security best practices. * Bachelor's degree in Computer Science, Information Systems, or a related field. --- Preferred Qualifications: * Snowflake SnowPro Core Certification or Advanced Architect Certification. * Experience integrating BI tools like Tableau, Power BI, or Looker with Snowflake. * Familiarity with real-time streaming technologies (Kafka, Kinesis, etc.). * Knowledge of Data Vault 2.0 or other advanced data modeling methodologies. * Experience with data cataloging and metadata management tools (e.g., Alation, Collibra). * Exposure to machine learning pipelines and data science workflows is a plus.

JobOpening Senior Data Engineer (Remote, Contract 6 Months) Remote | Contract Duration: 6 Months | Experience: 6-8 Years We are hiring a Senior Data Engineer for a 6-month remote contract position. The ideal candidate is highly skilled in building scalable data pipelines and working within the Azure cloud ecosystem, especially Databricks, ADF, and PySpark. You'll work closely with cross-functional teams to deliver enterprise-level data engineering solutions. #KeyResponsibilities Build scalable ETL pipelines and implement robust data solutions in Azure. Manage and orchestrate workflows using ADF, Databricks, ADLS Gen2, and Key Vaults. Design and maintain secure and efficient data lake architecture. Work with stakeholders to gather data requirements and translate them into technical specs. Implement CI/CD pipelines for seamless data deployment using Azure DevOps. Monitor data quality, performance bottlenecks, and scalability issues. Write clean, organized, reusable PySpark code in an Agile environment. Document pipelines, architectures, and best practices for reuse. #MustHaveSkills Experience: 6+ years in Data Engineering Tech Stack: SQL, Python, PySpark, Spark, Azure Databricks, ADF, ADLS Gen2, Azure DevOps, Key Vaults Core Expertise: Data Warehousing, ETL, Data Pipelines, Data Modelling, Data Governance Agile, SDLC, Containerization (Docker), Clean coding practices #GoodToHaveSkills Event Hubs, Logic Apps Power BI Strong logic building and competitive programming background Location : - Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune,Remote

JobOpening Senior Data Engineer (Remote, Contract 6 Months) Remote | Contract Duration: 6 Months | Experience: 6-8 Years We are hiring a Senior Data Engineer for a 6-month remote contract position. The ideal candidate is highly skilled in building scalable data pipelines and working within the Azure cloud ecosystem, especially Databricks, ADF, and PySpark. You'll work closely with cross-functional teams to deliver enterprise-level data engineering solutions. #KeyResponsibilities Build scalable ETL pipelines and implement robust data solutions in Azure. Manage and orchestrate workflows using ADF, Databricks, ADLS Gen2, and Key Vaults. Design and maintain secure and efficient data lake architecture. Work with stakeholders to gather data requirements and translate them into technical specs. Implement CI/CD pipelines for seamless data deployment using Azure DevOps. Monitor data quality, performance bottlenecks, and scalability issues. Write clean, organized, reusable PySpark code in an Agile environment. Document pipelines, architectures, and best practices for reuse. #MustHaveSkills Experience: 6+ years in Data Engineering Tech Stack: SQL, Python, PySpark, Spark, Azure Databricks, ADF, ADLS Gen2, Azure DevOps, Key Vaults Core Expertise: Data Warehousing, ETL, Data Pipelines, Data Modelling, Data Governance Agile, SDLC, Containerization (Docker), Clean coding practices #GoodToHaveSkills Event Hubs, Logic Apps Power BI Strong logic building and competitive programming background Location : - Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, Remote

We are looking for a highly skilled and experienced Senior Associate, Enterprise Integration Engineer to join our team in Bengaluru. The ideal candidate will have 2-7 years of experience in data migration, application development, or system integration. Roles and Responsibility Support the design and implementation of data migration and system integration projects. Collaborate with ERP, CRM, and HCM teams to gather and review business and technical requirements. Develop, test, and deploy integrations and data pipelines using modern integration platforms. Conduct unit testing and assist with QA to ensure technical solutions meet client needs and follow best practices. Take ownership of individual tasks and workstreams, delivering high-quality results within established timelines. Assist with preparing documentation related to design, testing, and implementation for client-facing and internal use. Job Requirements Bachelor's degree in Computer Science, Information Technology, Systems Engineering, or a related field. Minimum 2 years of experience in data migration, application development, or system integration. Experience with integration tools such as Boomi, Azure Integration Services (Azure Data Factory, Logic Apps, etc.), MuleSoft, SSIS, or Celigo. Strong analytical, problem-solving, and data wrangling skills, including the ability to clean, transform, and prepare data for integration, migration, or reporting. Familiarity with ERP, CRM, HCM, or CPM systems and their data structures. Solid understanding of software development principles and good documentation habits. Strong communication skills and ability to work collaboratively with cross-functional teams.

Build and deploy scalable ML models and MLOps pipelines in collaboration with data scientists Required Candidate profile 6–12 yrs in ML development, Python, model tuning, and enterprise AI deployment.

Python, software development & application & training of AI models, data pipelines, data structures & data integration LLM-based AI frameworks OpenAI CI/CD,serverlessAWS platforms, containerization, data structures, data platforms & data integration

Snowflake database administration designing data architecture, database networking, maintaining data security, configuring user access Python, git, SQL, AWS Snowflake data pipelines, data structures, data platforms, data integration, data governance

We are looking for a Senior Data Engineer who will design, build, and maintain scalable data pipelines and ingestion frameworks. The ideal candidate must have experience with DBT, orchestration tools like Airflow or Prefect, and cloud platforms such as AWS. Responsibilities include developing ELT pipelines, optimizing queries, implementing CI/CD, and integrating with AWS services. Strong SQL, Python, and data modeling skills are essential. The role also involves working with real-time and batch processing, ensuring high performance and data integrity.

We are looking for an experienced Software Developer with 5+ years of expertise in Java or Python for data processing and automation. The ideal candidate should have strong proficiency in Java, Spring, Microservices, and REST API development. Experience with cloud platforms, specifically Google Cloud Platform (GCP), is required. The candidate must have hands-on experience in creating IDE plugins for PyCharm, VS Code, IntelliJ, and web consoles. Additionally, proficiency in Python and data pipeline development is mandatory. The role demands a deep understanding of software development principles, automation, and scalable system design.

We are seeking a skilled Big Data Developer with 3+ years of experience to develop, maintain, and optimize large-scale data pipelines using frameworks like Spark, PySpark, and Airflow. The role involves working with SQL, Impala, Hive, and PL/SQL for advanced data transformations and analytics, designing scalable data storage systems, and integrating structured and unstructured data using tools like Sqoop. The ideal candidate will collaborate with cross-functional teams to implement data warehousing strategies and leverage BI tools for insights. Proficiency in Python programming, workflow orchestration with Airflow, and Unix/Linux environments is essential. Locations : Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, Remote

We are seeking a skilled Big Data Developer with 3+ years of experience to develop, maintain, and optimize large-scale data pipelines using frameworks like Spark, PySpark, and Airflow. The role involves working with SQL, Impala, Hive, and PL/SQL for advanced data transformations and analytics, designing scalable data storage systems, and integrating structured and unstructured data using tools like Sqoop. The ideal candidate will collaborate with cross-functional teams to implement data warehousing strategies and leverage BI tools for insights. Proficiency in Python programming, workflow orchestration with Airflow, and Unix/Linux environments is essential. Location: Remote- Delhi / NCR,Bangalore/Bengaluru,Hyderabad/Secunderabad,Chennai,Pune,Kolkata,Ahmedabad,Mumbai

AI/ML Architecture Development Implement and deploy machine learning models in production environments Work with generative AI models and NLP techniques (e.g., OpenAI, Claude APIs) Apply prompt engineering and retrieval-augmented generation (RAG) techniques Build end-to-end ML workflows from data preprocessing to model evaluation Contribute to the development of conversational AI solutions Software Engineering Data Pipeline Development Design, build, and maintain data pipelines and end-to-end ML workflows. Build and deploy web services that integrate ML models Implement APIs using frameworks like FastAPI or Flask Work with databases (preferably MySql) and data processing tools Ensure code quality, performance, and security in all implementations Deployment Integration Build production-grade ML models and APIs and deploy them on cloud platforms with the help of the DevOps team. Ability to Monitor, analyze, and optimize the performance of deployed models and data workflows with the help of Devops team Collaboration Work closely with cross-functional teams including data scientists and software engineers Contribute to a culture of learning and innovation Adapt to challenges even when requirements are ambiguous Technical Requirements: Programming Frameworks: Strong proficiency in Python with hands-on experience in TensorFlow, PyTorch, Keras, and related ML libraries/Ecosystem. Experience with data science tools (pandas, NumPymatplotlib, scikit-learn) Generative AI Expertise: Knowledge of generative AI models and frameworks, including OpenAI APIs, LangChain, LangGraph, Hugging Face Transformers, and related technologies. Experience in fine-tuning large language models (LLMs) and implementing RAG systems leveraging vector databases like Pinecone or similar. Experience in developing multi-agent Retrieval-Augmented Generation (RAG) applications, integrating automated workflows to streamline data retrieval,processing, and response generation. API Development: Experience in developing and deploying APIs using frameworks like FastAPI or Flask. Qualifications: Bachelor s degree in Computer Science, Engineering or related field. 5+ years of hands-on experience in AI/ML engineering, with expertise in generative AI and data engineering. Excellent problem-solving, analytical, and communication skills. Ability to work independently in a fast-paced, dynamic environment while effectively collaborating with cross-functional teams.

AI/ML Architecture Development Implement and deploy machine learning models in production environments Work with generative AI models and NLP techniques (e.g., OpenAI, Claude APIs) Apply prompt engineering and retrieval-augmented generation (RAG) techniques Build end-to-end ML workflows from data preprocessing to model evaluation Contribute to the development of conversational AI solutions Software Engineering Data Pipeline Development Design, build, and maintain data pipelines and end-to-end ML workflows. Build and deploy web services that integrate ML models Implement APIs using frameworks like FastAPI or Flask Work with databases (preferably MySql) and data processing tools Ensure code quality, performance, and security in all implementations Deployment Integration Build production-grade ML models and APIs and deploy them on cloud platforms with the help of the DevOps team. Ability to Monitor, analyze, and optimize the performance of deployed models and data workflows with the help of Devops team Collaboration Work closely with cross-functional teams including data scientists and software engineers Contribute to a culture of learning and innovation Adapt to challenges even when requirements are ambiguous Technical Requirements: Programming Frameworks: Strong proficiency in Python with hands-on experience in TensorFlow, PyTorch, Keras, and related ML libraries/Ecosystem. Experience with data science tools (pandas, NumPymatplotlib, scikit-learn) Generative AI Expertise: Knowledge of generative AI models and frameworks, including OpenAI APIs, LangChain, LangGraph, Hugging Face Transformers, and related technologies. Experience in fine-tuning large language models (LLMs) and implementing RAG systems leveraging vector databases like Pinecone or similar. Experience in developing multi-agent Retrieval-Augmented Generation (RAG) applications, integrating automated workflows to streamline data retrieval,processing, and response generation. API Development: Experience in developing and deploying APIs using frameworks like FastAPI or Flask. Qualifications: Bachelor s degree in Computer Science, Engineering or related field. 5+ years of hands-on experience in AI/ML engineering, with expertise in generative AI and data engineering. Excellent problem-solving, analytical, and communication skills. Ability to work independently in a fast-paced, dynamic environment while effectively collaborating with cross-functional teams.

We Are the Perfect Match If You: Have at least 1 year of experience in product data management , and hold an engineering degree . Have strong business acumen and product thinking, with the ability to translate data into actionable insights to drive business growth. Possess expertise in SQL , Advanced Excel , Google Sheets , and other database tools. Have experience working with large datasets and applying data engineering best practices . Are skilled in creating, managing, and optimizing data pipelines and data warehouses . Demonstrate the ability to convert raw data into actionable reports with real-time data fetching. Can build business use cases through thorough data analysis. Bring a strong background in data science , machine learning , and statistics , and can turn data into actionable strategies. Are detail-oriented, striving for perfection without compromising momentum. Thrive in collaboration and have the ability to communicate complex ideas across diverse teams to drive results. What Your Day Would Look: Drive the conversion of raw data into insights , enabling value based revenue streams for IDfy Build data-based hypothesis for insights specific to our risk product suite and run experiments based on the hypothesis Build products based on above insights, build Go-To-Market strategies for the product, hold client discussions for the same and drive adoption. Help PMs and SPMs prioritize product requirements for technical delivery Interact closely with technical teams to build products grounds-up, write test cases and take products live Implement best practices in data handling , ensuring accuracy, consistency, and availability of insights. Experience Range: 0 - 1 years Educational Qualifications: B.Tech/B.E Skills Required: Product Management

About We are hiring a Lead Data Solutions Engineer with expertise in PySpark, Python, and preferably Palantir Foundry. You will focus on transforming complex operational data into clear customer communications for Planned Power Outages (PPO) within the energy sector. Role & responsibilities Build, enhance, and manage scalable data pipelines using PySpark and Python to process dynamic operational data. Interpret and consolidate backend system changes into single-source customer notifications. Leverage Foundry or equivalent platforms to build dynamic data models and operational views. Act as a problem owner for outage communication workflows and edge cases. Collaborate with operations and communication stakeholders to ensure consistent message delivery. Implement logic and validation layers to filter out inconsistencies in notifications. Continuously optimize data accuracy and message clarity. Preferred candidate profile Ideal Profile 5+ years of experience in data engineering/data solutions. Strong command of PySpark, Python, and large-scale data processing. Experience in dynamic, evolving environments with frequent changes. Strong communication and collaboration skills. Ability to simplify uncertain data pipelines into actionable formats. Nice to Have Experience with Palantir Foundry, Databricks, or AWS Glue. Exposure to utility, energy, or infrastructure domains. Familiarity with customer communication systems, SLA governance, or outage scheduling.

We are looking for a highly skilled and experienced Azure Data Engineer with 2 to 7 years of experience to join our team. The ideal candidate should have expertise in Azure Synapse Analytics, PySpark, Azure Data Factory, ADLS Gen2, SQL DW, T-SQL, and other relevant technologies. ### Roles and Responsibilities Design, develop, and implement data pipelines using Azure Data Factory or Azure Synapse Analytics. Develop and maintain data warehouses or data lakes using various tools and technologies. Work with various types of data sources including flat files, JSON, and databases. Build workflows and pipelines in Azure Synapse Analytics. Collaborate with cross-functional teams to identify and prioritize project requirements. Ensure data quality and integrity by implementing data validation and testing procedures. ### Job Requirements Hands-on experience in Azure Data Factory or Azure Synapse Analytics. Experience in data warehouse or data lake development. Strong knowledge of Spark, Python, and DWH concepts. Ability to build workflows and pipelines in Azure Synapse Analytics. Fair knowledge of Microsoft Fabric & One Lake, SSIS, ADO, and other relevant technologies. Strong analytical, interpersonal, and collaboration skills. Must Have: Azure Synapse Analytics with PySpark, Azure Data Factory, ADLS Gen2, SQL DW, T-SQL. Good to have: Azure data bricks, Microsoft Fabric & One Lake, SSIS, ADO.

We are looking for a highly skilled and experienced Data Engineering Lead to join our team. The ideal candidate will have 5-10 years of experience in designing and implementing scalable data lake architecture and data pipelines. ### Roles and Responsibility Design and implement scalable data lake architectures using Azure Data Lake services. Develop and maintain data pipelines to ingest data from various sources. Optimize data storage and retrieval processes for efficiency and performance. Ensure data security and compliance with industry standards. Collaborate with data scientists and analysts to facilitate data accessibility. Monitor and troubleshoot data pipeline issues to ensure reliability. Document data lake designs, processes, and best practices. Experience with SQL and NoSQL databases, as well as familiarity with big data file formats like Parquet and Avro. Must have skills: Azure Data Lake, Azure Synapse Analytics, Azure Data Factory, Azure DataBricks, Python (PySpark, Numpy etc), SQL, ETL, Data warehousing, Azure Devops, Experience in developing streaming pipeline using Azure Event Hub, Azure Stream analytics, Spark streaming, and integration with business intelligence tools such as Power BI. Good to have skills: Big Data technologies (e.g., Hadoop, Spark), Data security. General Skills: Experience with Agile and DevOps methodologies and the software development lifecycle, proactive and responsible for deliverables, escalates dependencies and risks, works with most DevOps tools, limited supervision, completes assigned tasks on time and provides regular status reports, trains new team members, and builds strong relationships with project stakeholders. ### Job Requirements Minimum 5 years of experience in designing and implementing scalable data lake architecture and data pipelines. Strong knowledge of Azure Data Lake, Azure Synapse Analytics, Azure Data Factory, Azure DataBricks, Python (PySpark, Numpy etc), SQL, ETL, Data warehousing, and Azure Devops. Experience in developing streaming pipelines using Azure Event Hub, Azure Stream analytics, and Spark streaming. Familiarity with big data file formats like Parquet and Avro. Ability to work with multi-cultural global teams and virtually. Knowledge of cloud solutions such as Azure or AWS with DevOps/Cloud certifications is desired. Proactive and responsible for deliverables. Escalates dependencies and risks. Works with most DevOps tools, limited supervision. Completes assigned tasks on time and provides regular status reports. Trains new team members and builds strong relationships with project stakeholders.

We are looking for a highly skilled and experienced Senior Data Scientist with 3 to 8 years of experience to join our team in Bengaluru. The ideal candidate will have a strong background in applied mathematics, statistics, or data science, with excellent presentation and communication skills. ### Roles and Responsibility Support the Lead Data Scientist and team members in solving problems, analyzing data, and finding solutions. Lead the design, development, and deployment of advanced statistical methods, data science/ML, and other quantitative techniques to solve complex business problems. Collaborate with cross-functional teams to integrate data-driven insights into business strategies and operations. Oversee and drive the lifecycle of statistical and AI/ML decision support solutions and products, ensuring successful and timely delivery. Present data-driven insights and strategic recommendations to senior management and key stakeholders. Develop and maintain large-scale data systems, including data pipelines, architectures, and governance frameworks. ### Job Requirements Bachelor's degree in applied mathematics, statistics, applied mathematics, physics, economics, or other quantitative fields; a master's degree is preferred. Minimum 3 years of experience in Statistics, AI/Machine Learning/Data Science in technology companies, Life Sciences, Pharma, Biotech, or relevant regulated industries (banking, insurance, etc.). Solid understanding of applied statistical modeling, applied math modeling, and ML techniques, including clustering, classification, regression, dimensionality reduction, ensemble methods, and natural language processing. Proficiency in programming languages such as Python, PySpark, or R for data curation, transformation, analysis, modeling, and visualization tasks. Experience leading a team of Data Scientists, Data Analysts, or Data Engineers. Excellent presentation and communication skills, with the ability to communicate complex technical concepts to both technical and non-technical audiences.

We are looking for a skilled Data Engineering Lead with 8 to 10 years of experience, based in Bengaluru. The ideal candidate will have a strong background in designing and implementing scalable data lake architecture and data pipelines. ### Roles and Responsibility Design and implement scalable data lake architectures using Azure Data Lake services. Develop and maintain data pipelines to ingest data from various sources. Optimize data storage and retrieval processes for efficiency and performance. Ensure data security and compliance with industry standards. Collaborate with data scientists and analysts to facilitate data accessibility. Monitor and troubleshoot data pipeline issues to ensure reliability. Document data lake designs, processes, and best practices. Experience with SQL and NoSQL databases, as well as familiarity with big data file formats like Parquet and Avro. Experience in developing streaming pipelines using Azure Event Hub, Azure Stream analytics, Spark streaming. Experience in integrating with business intelligence tools such as Power BI. ### Job Requirements Strong knowledge of Azure Data Lake, Azure Synapse Analytics, Azure Data Factory, and Azure DataBricks. Proficiency in Python (PySpark, Numpy), SQL, ETL, and data warehousing. Experience with Agile and DevOps methodologies and the software development lifecycle. Proactive and responsible for deliverables; escalates dependencies and risks. Works with most DevOps tools, limited supervision, and completes assigned tasks on time with regular status reporting. Ability to train new team members and build strong relationships with project stakeholders. Knowledge of cloud solutions such as Azure or AWS with DevOps/Cloud certifications is desired. Ability to work with multi-cultural global teams virtually. Completion of assigned tasks on time and regular status reporting.