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Build and maintain scalable data pipelines on Databricks (Delta Lake, Spark) to feed analytics and ML systems, troubleshoot production issues, and optimize costs for a fintech investing platform.
Build and maintain robust data pipelines on AWS to process terabytes of media audience, adserver, and CRM data, enabling predictive products and ad-revenue insights.
Build and scale high-volume data pipelines for an industrial IoT platform on AWS, using Spark/Flink, Kinesis, Databricks, and FastAPI to deliver real-time and batch analytics.
Senior Data Engineer building and optimizing AWS and Databricks pipelines for JPMorgan Chase, focusing on scalable ETL, Spark/Databricks, and cloud cost governance.
Build and maintain batch and real-time data pipelines on Databricks using PySpark, SQL, Azure, and Delta Lake while optimizing costs and resolving production issues.
Build and maintain ETL/ELT pipelines in Azure Data Factory and Databricks, ingesting and transforming data into clean, analytics-ready datasets using PySpark, SQL, and cloud storage.
Senior Data Engineer builds and migrates data pipelines for a life-sciences CRM transition, using Databricks, AWS S3, dbt, and Airflow to move and transform Salesforce/Veeva data into a cloud data warehouse.
Build and maintain reliable data pipelines and a Lakehouse architecture on Databricks to feed analytics, models, and APIs, while integrating AI/ML solutions and mentoring peers.
Build and maintain scalable data pipelines and models in Databricks to power analytics and ML, using Python, SQL, and Spark while mentoring peers.
Build and maintain scalable, reliable data infrastructure using ClickHouse, CockroachDB, Trino, and Kubernetes, plus AWS services and Terraform.
Designs and maintains scalable data pipelines using PySpark and Delta Lake on Databricks to enable reliable data enrichment across platforms.
Lead a team to design, build, and optimize Databricks-based data pipelines and AI architectures for enterprise clients, ensuring scalable data ingestion, processing, and visualization while mentoring engineers.
Senior Data Engineer builds and operates a Spark-based Lakehouse platform (Databricks, Delta Lake, Azure) using Scala/Spark pipelines and cloud infrastructure.
Design and maintain high-volume IoT data pipelines on AWS, combining real-time and batch processing with Spark/Flink, and expose analytics-ready APIs in Python.
Senior Data Engineer designs data architectures and Databricks pipelines for a major retail company, builds ML/AI agents, and supports Power BI analytics.
Build and maintain scalable ETL/ELT pipelines on Databricks (Spark SQL, PySpark, Scala) to feed reliable, high-performance data for analytics and decision-making.
Lead a team migrating legacy data systems to a modern Databricks/Azure platform, building scalable batch and streaming pipelines, and deploying BI, ML, and GenAI use cases for a large financial client.
Build and optimize ETL/ELT pipelines on Databricks using Spark SQL, PySpark, and Scala, and set up a Lakehouse with Delta Lake for reliable, secure data delivery.
Build and maintain robust data pipelines on AWS to centralize and process terabytes of media audience, adserver, CRM, and radio data, using Python, PySpark, and SQL to deliver actionable insights and KPIs for advertising, streaming, and CRM teams.
Build and maintain scalable ETL/ELT pipelines on Databricks using Spark SQL, PySpark, and Scala to feed reliable, high-performance data for analytics and decision-making.
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