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Leads quality engineering for an enterprise AI platform, building test frameworks for Agentic AI workflows and LLM-based systems using Python, Java, and modern CI/CD stacks.
Build and maintain AWS-native data pipelines and warehouses for telecom analytics using S3, Redshift, Glue, and Python/SQL.
Design and build scalable, cloud-native data pipelines and data-lake architectures on AWS using S3, Glue, Redshift, and Kinesis.
Builds Python-based data pipelines and AI/ML integrations for life-science labs, translating assay workflows into Benchling, AWS, and FastAPI services while ensuring regulatory compliance.
Build and maintain Snowflake data models to power AI-driven marketing systems, enabling agentic workflows and LLM tool-calling for predictive and generative use cases.
Design and build scalable AWS data pipelines and real-time streaming systems using Confluent Kafka for analytics and AI workloads.
Lead a team building PySpark/AWS ETL pipelines that ingest SAP, Intelex, SQL and OSI PI data into a cloud data lake and ensure clean, reliable data flows for analytics.
Build and scale a cloud-native data platform on AWS to power real-time recommendations and analytics for Europe’s leading brands.
Build and maintain data pipelines for trade and communications surveillance, ensuring regulatory compliance and data quality across AWS infrastructure.
Designs and deploys ML models for localization workflows using Python, TensorFlow, and AWS services; owns projects from conception to production.
Build and maintain cloud-native AWS data platforms, ETL/ELT pipelines, and data lakes to support analytics and BI use cases.
Build and maintain scalable, real-time data pipelines on AWS and Databricks using Kafka, Spark, Flink, and Airflow, ensuring high-throughput data processing and quality.
Build and maintain scalable data pipelines on Databricks and AWS, focusing on ETL, real-time streaming with Spark/Kafka, and cloud infrastructure optimization.
Senior Data Engineer builds and operates AWS-based financial data platforms, cloud infrastructure, and AI agents for accounting automation, while directly engaging with clients to design and deploy solutions.
Designs and maintains data pipelines and warehouses, transforming raw data into insights using Oracle, PySpark, and Azure SQL for AI-driven analytics.
Build and migrate ETL/ELT pipelines on Databricks and AWS for a global fund-services provider, using Delta Lake, Spark, and AWS Glue.
Design and build serverless data pipelines and cloud infrastructures using Python, AWS, and Infrastructure as Code for enterprise-scale data solutions.
Lead the end-to-end data architecture—ingestion, processing, modeling, and consumption—using Python, PySpark, Airflow, and AWS services to enable reliable reporting and LLM-driven analytics at scale.
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