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Data Engineer owning and extending a Databricks Lakehouse (medallion pipelines, Unity Catalog) that powers AI agent products for higher education clients, using Spark/PySpark, Python, SQL, and AWS.
Lead Data Engineer architecting scalable data pipelines and ELT processes using Databricks, Apache Spark, and Delta Lake, while mentoring a team of engineers at a data-focused technology services company.
Build and maintain scalable cloud data platforms using Azure and Databricks, developing ETL/ELT pipelines with SQL and Python/PySpark in a senior individual contributor role.
Design, build, and maintain scalable cloud-based data pipelines using Databricks, Apache Spark, Python, and SQL for Energy Trading & Risk Management clients.
Senior Data Engineer leading the re-engineering and validation of an existing Azure Synapse enterprise data platform and driving its migration to Databricks, focused on reverse-engineering complex pipelines, ensuring data governance, and implementing lakehouse architectures.
Lead/Senior Data Engineer designing and delivering scalable data pipelines and platforms using Python, Scala, Spark, and SQL, while mentoring a team and collaborating cross-functionally.
Senior/Lead Data Engineer building and optimizing scalable data platforms and pipelines using Databricks, PySpark, Delta Lake, and AWS/Azure Cloud.
Data Engineer building and optimizing scalable data pipelines and architectures on Azure using Databricks, PySpark, Delta Lake, and CI/CD/DataOps practices.
Senior Data Engineer on a 6-month contract building and maintaining automated ETL/ELT data pipelines for data governance and analytics, primarily using Azure Databricks, Azure Data Lake, and Microsoft Purview.
Senior Data Engineer owning data pipelines end to end on a Microsoft Fabric Lakehouse platform, building batch/incremental PySpark pipelines, dimensional models, and Power BI semantic layers with a strong emphasis on data quality and operational excellence.
Senior Data Engineer building production Databricks Lakehouse platforms with PySpark, dbt, PostgreSQL, and CI/CD pipelines at Publicis Global Delivery in India.
Build and maintain scalable data pipelines using Spark, Scala, Airflow, and Azure Databricks in a hybrid role based in Bengaluru. Work with modern data lakehouse technologies, containerization, and CI/CD practices.
Design, build, and support scalable data pipelines and integration solutions for a major bank using Databricks, Spark/PySpark, SQL, and Azure data services to enable analytics and reporting.
Design and build end-to-end data engineering solutions on Microsoft Fabric (Lakehouse, Dataflows Gen2, Pipelines) and Azure (ADLS Gen2, ADF, Synapse) using PySpark and SQL, with CI/CD via Azure DevOps.
Senior Data Engineer building and operating production-grade data pipelines on AWS (S3, Glue, EMR, Redshift, Lambda) using Python and SQL, with Airflow, Delta Lake, and streaming tools, for a political/policy research analytics firm in Bangalore (hybrid).
On-site Microsoft Fabric Data Engineer in Noida (evening shift 2–11 PM IST) building and supporting data pipelines, Lakehouse architectures, and Power BI semantic models using Python, PySpark, and SQL.
Senior Data Engineer designing, building, and operating data pipelines and a lakehouse platform on Databricks and Microsoft Fabric using Spark, Python, and SQL.
Data Engineer developing scalable ETL/ELT pipelines, Azure Data Factory workflows, and Snowflake data warehouse solutions using PySpark, Databricks, and Delta Lake architecture to support BI and AI initiatives.
Data Engineer designing, developing, and maintaining scalable ETL/ELT pipelines, data warehouses, and data lakes using SQL, Python, and Big Data technologies (Spark, Databricks) on Azure/cloud platforms for an Azure-focused managed services company.
Lead Data Engineer designing and building scalable batch and real-time data pipelines using Scala, Apache Spark, SQL, Kafka, and cloud platforms (AWS/Azure/GCP).
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