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Build and maintain cloud-based data pipelines and analytics solutions on AWS using Python and SQL, integrating AI models into business-facing data systems.
Build and run end-to-end data pipelines for enterprise clients, designing ETL workflows, cloud data models, and dashboards while mentoring junior engineers.
Design, build, and maintain scalable data pipelines and architectures using Python, SQL, Spark, and cloud platforms to enable analytics and data-driven decisions.
Design and scale high-performance ELT pipelines for a centralized data warehouse, collaborating with cross-functional teams to build a robust, scalable data platform.
Senior Data Engineer builds and scales reliable, high-quality data pipelines and governance at a global market-research analytics firm using Python, SQL, Airflow, Spark, and AWS.
Build and maintain ETL pipelines, optimize MongoDB schemas, and create Metabase dashboards to power AI-driven travel rental analytics and reporting.
Build and maintain scalable data pipelines using cloud platforms (AWS/Azure/GCP), Databricks, and tools like Spark and DBT to integrate and optimize data workflows for enterprise clients.
Build and maintain scalable data pipelines using cloud platforms (AWS/Azure/GCP), Databricks, and tools like Spark and DBT to integrate and transform data for clients.
Build and scale data pipelines, warehouses, and analytics to power a fast-growing second-hand marketplace, analyzing pricing, supply, and conversion to drive business decisions.
Build and maintain AWS-based data pipelines that ingest and transform structured data into Redshift using PySpark, SQL, and ETL/ELT tools.
Build and optimize scalable data pipelines and analytics infrastructure using Python, Spark, Airflow, and ClickHouse to power Atolls' global shopping platform.
Build and improve Veeva Link’s data pipelines and cloud-based data platform using Java/Python, Spark, and cloud services to power life-sciences expert matching and clinical-trial outreach.
Build and deploy production-grade AI systems end-to-end, from data pipelines and ML models to scalable deployment and monitoring using Python, PyTorch, and MLOps tools.
Maintains and scales AWS cloud infrastructure for data analytics projects, automates deployments with CI/CD, and ensures security and cost efficiency.
Build and maintain AWS-based ETL pipelines for a banking client, migrating legacy systems to a Lakehouse architecture using PySpark and Python.
Builds scalable, secure cloud data pipelines on AWS using services like Glue, RDS, Redshift, and Kinesis.
Build and maintain cloud data pipelines for a banking client, migrating legacy systems to AWS (S3, Redshift, Athena) using Python, PySpark, and AWS Glue.
Senior Data Engineer builds and optimizes AWS-based data pipelines for a financial-sector client, using DBT, Airflow, Glue, Redshift and Python to transform and validate large datasets.
Designs and maintains data pipelines, ETL processes, and data warehouses to support analytics and business intelligence using SQL, Python, and cloud platforms.
Own and evolve the data warehouse stack (Matillion, Redshift, Tableau), design sustainable business data models, and build optimized ETL pipelines to power reporting and analytics for an adtech company.
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