Azure Data Engineer Support

I’m looking for ongoing, hands-on help from a seasoned data engineer who can jump into my day-to-day workload. Azure is the centrepiece of the stack, so you’ll need to feel at home configuring storage solutions and spinning up efficient data pipelines. On-prem integrations are still handled through SSIS/SSRS, so you’ll also be maintaining and fine-tuning existing packages while building new ETL flows when business requirements change.

Where Python fits in: I occasionally automate data quality checks and lightweight transformations with scripts, so an ability to write clean, production-ready Python that plugs into both Azure services and SSIS script tasks is important.

Core scope
• Azure – provision and manage storage resources, then design and deploy reliable pipelines that move data between on-prem sources, the cloud, and downstream analytics layers.
• SSIS/SSRS – develop new ETL packages, troubleshoot or refactor the old ones, and keep nightly jobs running smoothly.
• Python – create reusable scripts for data validation, orchestration helpers, and quick ad-hoc analyses.

A typical week might include debugging a failed SSIS job, migrating a data mart to Azure storage, and documenting the changes so I can present them to stakeholders. I’ll share access via VPN/remote desktop and stay available on Slack for quick questions or pair-sessions.

Deliverables are straightforward:
1. Working SSIS/SSRS packages with deployment scripts and rollback plans.
2. Azure resources (storage accounts, pipelines) deployed in my subscription and fully documented.
3. Python utilities committed to the repo with clear usage notes.

Please outline recent projects that combine Azure data services with SSIS, and let me know your general availability for collaboration across US Eastern hours.