Senior Data Engineer in United

We’re looking for a Senior Data Engineer to design, build, and operate modern data platforms at scale. You’ll work across Azure, Microsoft Fabric, and AWS - building reliable pipelines, performant data models, and self-service analytics that drive real business decisions. A core part of this role is containerized workload execution: designing and deploying pipeline jobs using Azure Container Apps Jobs for scheduled and event-driven processing. This is a hands-on role for an engineer who thrives in ambiguity, values clean architecture, and moves comfortably between strategy and implementation., n \n

• Develop Python-based ETL/ELT pipelines ingesting data from APIs, flat files, databases, and SaaS platforms \n

• Build and deploy containerized jobs using Azure Container Apps Jobs, including scheduling, scaling rules, secrets management (Key Vault), and Container Registry integration \n

• Maintain data movement between on-premises SQL Server and cloud targets \n

• Design idempotent, fault-tolerant pipeline patterns with robust logging, alerting, and retry logic \n

• Partner with analytics teams to deliver clean, well-documented data models for Power BI and similar BI tools \n

• 5-8 years of hands-on data engineering in production environments \n

• Proven track record delivering data platforms on Azure and/or AWS \n

• Experience migrating legacy on-premises infrastructure to cloud- solutions \n

• Hands-on experience with Azure Container Apps Jobs or a comparable containerized job execution platform \n

• Design and build scalable data pipelines using Python and cloud- orchestration tools (Azure Data Factory, Azure Container Apps Jobs, Fabric Data Pipelines) \n

• Architect solutions across Microsoft Fabric Warehouses, Azure SQL, and AWS (S3, Redshift), selecting the right tool for the workload \n

• Implement Medallion/layered architecture (Bronze * Silver * Gold) for structured, governed data delivery \n

• Manage and optimize large-scale data warehouse environments for performance, cost, and maintainability \n

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• Python - production-grade pipelines, transformations, and automation \n

• SQL - advanced T-SQL and ANSI SQL; SQL Server, Azure SQL, Redshift, and Fabric query engines \n

• Microsoft Fabric - Warehouses, Lakehouses, Data Pipelines, OneLake \n

• Azure - ADF, Azure SQL, ADLS, Key Vault, Container Apps Jobs, Container Registry \n

• Containerization - Docker image development, container registry management, Container Apps Jobs (scheduling, scaling, secret injection) \n

• AWS - S3 for data lake storage, Redshift for cloud warehousing \n

• Data Modeling - dimensional modeling, star/snowflake schema, ER modeling for OLTP and OLAP