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.
About the Role
- Design and build scalable data pipelines using Python and cloud‑native orchestration tools (Azure Data Factory, Azure Container Apps Jobs, Fabric Data Pipelines)
- Architect solutions across Microsoft Fabric Warehouses, Azure SQL, and AWS (S3, Redshift), selecting the right tool for the workload
- Manage and optimize large-scale data warehouse environments for performance, cost, and maintainability
Responsibilities
- Develop Python-based ETL/ELT pipelines ingesting data from APIs, flat files, databases, and SaaS platforms
- Build and deploy containerized jobs using Azure Container Apps Jobs, including scheduling, scaling rules, secrets management (Key Vault), and Container Registry integration
- Maintain data movement between on‑premises SQL Server and cloud targetsDesign idempotent, fault‑tolerant pipeline patterns with robust logging, alerting, and retry logic
- Partner with analytics teams to deliver clean, well‑documented data models for Power BI and similar BI tools
Qualifications
- 5–8 years of hands‑on data engineering in production environments
- Proven track record delivering data platforms on Azure and/or AWS
- Experience migrating legacy on‑premises infrastructure to cloud‑native solutions
- Hands‑on experience with Azure Container Apps Jobs or a comparable containerized job execution platform
Required Skills
- Python — production‑grade pipelines, transformations, and automation
- SQL — advanced T‑SQL and ANSI SQL; SQL Server, Azure SQL, Redshift, and Fabric query engines
- Microsoft Fabric — Warehouses, Lakehouses, Data Pipelines, OneLake
- AWS — S3 for data lake storage, Redshift for cloud warehousing
- Data Modeling — dimensional modeling, star/snowflake schema, ER modeling for OLTP and OLAP
Preferred Skills
- Microsoft Fabric in production (Fabric Warehouses, OneLake integration)
- dbt or similar transformation frameworks
- Cloud certifications: DP-203 (Azure Data Engineer), AWS Certified Data Analytics, or equivalent
- Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field — or equivalent professional experience