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Principal AI Data Engineer builds and deploys GenAI/AgenticAI systems on Azure and Databricks, focusing on RAG, AI agents, and scalable workflows.
Design and build scalable AWS data pipelines (ETL, data lakes, warehouses) using Python, Spark, and AWS services like Glue, RedShift, and Kinesis to process large datasets for clients across multiple sectors.
Senior Data Engineer builds and optimizes cloud-based data pipelines and warehouses using SQL, Python, and Microsoft Fabric/Synapse to enable analytics and reporting for a large organization.
Data Analyst role in Glasgow for a fintech client; daily tasks include Python, PySpark, SQL, and data profiling to support banking systems and MDM tools.
Lead a team building production-grade AI/ML systems and data pipelines for clients, focusing on clean code, scalable architectures, and end-to-end ownership using Python/Scala and big-data stacks like Spark and Snowflake.
Build and maintain cloud-based data pipelines and warehouses using Azure Databricks, Snowflake, and AWS services to enable AI/ML-driven insights for enterprise clients.
Design and deliver enterprise Snowflake data platforms, lead client-facing technical discussions, and optimize cloud data solutions for large-scale transformations.
Leads a team to design, build, and optimize data pipelines that transform raw data into insights using SQL, Python, ETL tools, and cloud data services.
Build and maintain scalable data pipelines and warehousing solutions using Databricks, Spark, and AWS tools to support HR analytics and business intelligence at a global financial firm.
Lead the architecture and engineering of a modern, cloud-native data platform for State Street’s investment management business, using Python, Spark, Snowflake/Databricks, and Apache Iceberg to build scalable analytics and governance capabilities.
Build and maintain Porch Group’s Agentic Platform: retrieval pipelines, remote agent deployment, MCP servers, and LLM evaluation on Python/TypeScript/Kubernetes/GCP, enabling AI across JVM-based services.
Build and maintain CI/CD pipelines, Kubernetes/OpenShift clusters, and big-data platforms (Hadoop, Spark, Kafka) to automate deployments and ensure scalable, secure data processing.
Build and maintain ING’s Spring Boot-based API SDK, a core framework for secure, resilient APIs powering global digital banking, integrating with service mesh, security, and observability platforms.
Senior engineer building scalable data pipelines and cloud solutions for healthcare analytics using Python, Spark, and Azure.
Business Analyst for a banking API platform, documenting requirements, analyzing data flows, and bridging business needs with development teams in an Agile environment.
Builds and optimizes cloud-based big-data pipelines and warehouses using Python, PySpark, and SQL/NoSQL databases for clients of this IT services provider.
Build and optimize cloud-based big data pipelines and data warehouses using Python, PySpark, and SQL/NoSQL databases for clients.
Build and enhance a big-data post-trade system in Java, processing high-volume XML messages via IBM MQ and ingesting data into HDFS/HBase with Spark and Scala.
Build and maintain scalable data pipelines in Azure (Databricks, ADF) using Scala, Python, and SQL; design enterprise data warehouses and optimize ETL/ELT workflows for insurance and healthcare analytics.
Build and scale Kotak’s next-gen AWS-based data lakehouse, designing pipelines, ETL workflows, and governance for a 100+ member team revamping the bank’s entire data platform.
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