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Build and own a new HR data warehouse, then transition into analytics to help HR teams make data-driven workforce decisions using SQL, Python, and cloud pipelines.
Leads AI data engineering at a Singapore government agency, designing scalable data pipelines and governance for AI systems that support national security.
Build and optimize Plaud’s data platform to power AI-driven productivity tools, focusing on data warehousing, ETL/ELT, governance, and cloud services.
Build AI-ready data pipelines and knowledge systems for an investment firm’s agentic AI, integrating structured financial data, unstructured research, and real-time feeds into vector stores, graph databases, and retrieval pipelines.
Designs and builds cloud data pipelines on AWS and Databricks, architecting storage solutions and optimizing ETL workflows for analytics and reporting.
Designs and builds scalable AWS data pipelines using Glue, Redshift, and S3, implementing ETL/ELT workflows and optimizing for performance and reliability.
Design and build scalable data pipelines and platforms to power analytics and AI solutions using cloud technologies like AWS, Databricks, and Snowflake.
Build and maintain scalable data pipelines and AI/ML platforms using AWS, Snowflake, and Databricks to support analytics and model delivery.
Design and build cloud-based data analytics infrastructure using AWS, Databricks, and IDMC, migrating and modernizing healthcare data pipelines and ETL workflows.
Build and maintain scalable data pipelines for a global crypto exchange, enabling AML monitoring, KYC/KYB, sanctions screening, and regulatory reporting with AI-assisted engineering and strict auditability.
Designs and maintains cloud-based data pipelines and warehouses using AWS, Databricks, and Informatica to support healthcare analytics and reporting.
Build and maintain scalable data systems, design ETL/ELT pipelines, and optimize data quality using AWS, Python, SQL, and Spark for analytics and ML workloads.
Designs and maintains scalable data pipelines and cloud-based data warehouses to feed analytics and AI models, using Python, Spark, Kafka, and cloud platforms like AWS/Azure/GCP.
Build and maintain a Linux-based, AWS-hosted data platform using Java, Spark EMR, Kafka, Scala and Angular to power a financial firm’s data warehouse and BI tools.
Design and run Databricks-based data/ML platforms on AWS for a financial-crime product, focusing on governance, security, and DevSecOps rather than Spark coding.
Build and optimize data pipelines for semiconductor manufacturing using AWS, PySpark, Redshift, and Python to support analytics and AI initiatives across global fabs.
Build and maintain AWS-based infrastructure and CI/CD pipelines using CloudFormation and Jenkins, with Python scripting and container expertise.
Design and build modern data analytics, Big Data, and data-warehouse solutions in AWS, GCP, or Azure, including ETL/ELT pipelines and governance using Databricks, Snowflake, and Spark.
Builds and maintains a global digital-ad platform using Python (FastAPI/Flask) and TypeScript (React/Vue), working with microservices, SQL/NoSQL, and cloud tooling to serve millions of users.
Senior AI Data Engineer builds and maintains scalable ELT pipelines and dbt models for Zendesk’s analytics platform, integrating AI tools to enhance data delivery and team productivity.
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