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Designs scalable Azure data architectures and builds and maintains data pipelines, transforming data and ensuring quality across systems. Core stack: Azure Data Lake, SQL Data Warehouse, Data Factory, Fabric, with SQL or Python and DevOps.
Data engineer designing scalable data architectures and building ETL pipelines on Microsoft Azure (Fabric, Data Factory, Data Lake, SQL Data Warehouse), handling integration, storage optimization, security, and monitoring using SQL/Python and DevOps. Requires 3+ years of IT/data engineering experience; SAP Datasphere and AI-assisted tasks preferred.
Senior Data Engineer building scalable data pipelines and production AI/GenAI workflows (RAG, vector databases, LLM integration) using Python, SQL, Spark/Databricks, Airflow, cloud platforms, and MLOps/LLMOps practices. Full-time, permanent, office-based in London five days a week, with mentoring and technical leadership duties.
Designs and builds enterprise-scale data warehouses and ETL/ELT pipelines (Python, SQL) for finance and loan data in the banking domain. Day to day involves dimensional data modeling, source-to-target mapping, data quality/reconciliation work, and supporting cloud data platform modernization.
A 6–12 month contract Data Engineer role in Bangalore designing and building scalable batch and real-time data pipelines. Day-to-day work centers on Scala, Apache Spark (including Structured Streaming), and Kafka, alongside Hive, SQL, S3, Presto, and Delta Lake on cloud data infrastructure.
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