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Lead Data Engineer overseeing enterprise-scale ETL and data modernization projects, architecting pipelines with Python, PySpark, Informatica, Databricks, Snowflake, ADF, and AWS Glue while mentoring a team of data engineers.
Databricks Data Engineering Architect defines and drives Databricks architecture and strategy, takes end-to-end ownership of Databricks solutions from design through implementation, and works with technologies like Databricks, Spark, Delta Lake, SQL, Python/PySpark, and Lakeflow.
GCP Data Engineer responsible for designing, building, and maintaining scalable data pipelines, data warehouses, and big data solutions on Google Cloud using Dataflow, BigQuery, Cloud Composer, and related GCP services.
Technical Lead driving the migration of Microsoft/Azure data platforms to Databricks, providing hands-on mentorship, architecture oversight, and pipeline development for the data engineering team.
Lead Data Engineer at IndusInd Bank in Mumbai, architecting and building a cloud-native Azure Databricks data platform with PySpark, leading a team of data engineers and analysts to deliver scalable lakehouse architectures and BI solutions.
Senior Data Engineer designing and maintaining real-time and batch data pipelines for SMC Global Securities' financial services and trading platforms, using SQL, Python, AWS (S3, Redshift, Athena, Glue, EMR, Lambda), Airflow, DBT, and Spark within Data Lakehouse architectures.
Data Engineer building and optimizing ETL/ELT pipelines with SQL and Python to create analytics-ready datasets for the Analytics team.
Design, build, and maintain the analytics data layer—pipelines (Airflow), warehouse (BigQuery), and ETL—on GCP, applying software engineering best practices to deliver BI solutions.
Senior Data Engineer building real-time data ingestion/processing pipelines and large-scale enterprise data solutions using PySpark, Python, Airflow, SQL, and AWS big data services.
Lead and hands-on build data & analytics solutions using Databricks, Informatica, and Tableau on AWS for Eisai's global pharmaceutical data platform, driving BI, AI, and data democratization.
Data Engineer designing, building, and supporting scalable data pipelines and integration solutions using Databricks, Spark/PySpark, SQL, and Azure data services for a major North American bank's tech hub in Hyderabad.
Design and build data pipelines and data models on Azure, Databricks, Snowflake, and Postgres to support AI/ML and computer-vision workflows for a digital transformation services company.
Senior Data Engineer designing and maintaining enterprise-scale data ingestion and integration solutions using Microsoft Fabric, Azure Data Services, SQL Server, and ETL/ELT pipelines.
Azure Data Engineer role at TCS Noida involving data ingestion, transformation, storage, warehousing, and modeling using Azure cloud services like Data Factory, Databricks, Synapse Analytics, and Python/PySpark.
Data Engineer building scalable data pipelines and enterprise integrations using Adobe Experience Platform (AEP) and AWS to enable trusted customer data across digital ecosystems.
Design, develop, and optimize big data ETL pipelines using Apache Spark and Databricks on Azure cloud, while collaborating with analysts and implementing CI/CD and security best practices.
Senior Databricks Data Engineer responsible for migrating enterprise data platform from Informatica to Azure Databricks, developing data pipelines using PySpark and SQL, and implementing Delta Lake architecture with Medallion principles.
Design, build, and support scalable data pipelines and integration solutions using Azure Databricks, Spark/PySpark, and Delta Lake for a major bank's analytics, reporting, and risk management needs.
Data Engineer building scalable data ingestion and integration pipelines on Adobe Experience Platform (AEP) and Google Cloud Platform (GCP), collaborating with architects to deliver production-ready data solutions for enterprise customer data ecosystems.
Lead Data Engineer building data pipelines for analytics and data science use cases on Big Data platforms, primarily using Spark, Scala, Hadoop, and Hive.
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