Sr. Data Engineer (SQL / Databricks / PySpark)

TalentOla • Chicago, IL

1d • Hybrid

About The Position

Seeking a Senior Data Engineer with deep expertise in SQL Server, Azure SQL, and Databricks to design, optimize, and deliver scalable cloud-based data solutions supporting analytics and enterprise data platforms.

Requirements

• Strong understanding of ETL / ELT Concepts including pipeline patterns, incremental loads, data validation, and troubleshooting.
• Advanced SQL querying (CTEs, views, joins, complex query logic) and performance tuning for transformations and validation.
• Production-quality Python development (modular code, testing, logging, integration with APIs/files, CICD, Unit Test/Integration test automation, Code Coverage).
• PySpark for distributed transformations and performance optimization (joins, partitions, debugging), CICD, Unit Test/Integration test automation, Code Coverage.
• Experience building/operating Azure Data Factory (ADF) pipelines, parameterization, triggers, monitoring, retry/error handling; integrate with Databricks/ADLS.
• Experience developing and operationalizing Databricks notebooks/jobs/workflows; Delta Lake patterns; basic cluster/job configuration.
• Hands-on experience with Azure Fundamentals including ADLS Gen2, Azure Portal, Storage Explorer, Resource Groups, Azure SQL, and familiarity integrating with Azure OpenAI.
• Ability to use/maintain Pulumi scripts for provisioning and managing Azure resources across environments.
• 10+ Years of experience.
• Engineering Degree – BE/ME/BTech/MTech/BSc/MSc.

Nice To Haves

• Ability to support/translate validation rules with SQL scripts and create data quality reports.
• TypeScript: Useful for pulumi pipeline to create Azure components.
• Java: Useful for integration with existing services/components.
• .NET: Useful for integration with existing services/components.
• Angular / Spring Boot: Minor troubleshooting or coordination with app teams.
• Clinical (Health care) domain experience.
• Technical certification in multiple technologies is desirable.

Responsibilities

• Design, build, and support end-to-end data pipelines (ingestion, transformation, validation, publishing).
• Develop and optimize SQL and PySpark/Databricks transformations for large datasets.
• Build production-grade Python components (reusable modules, logging, error handling, testing).
• Create and maintain Azure Data Factory (ADF) pipelines (triggers, parameterization, monitoring, failure handling).
• Work within Azure environments (ADLS Gen2, Azure SQL, resource groups, portal operations).
• Provision and maintain Azure components using Pulumi (Infrastructure as Code).
• Participate in code reviews, documentation, and operational support (triage + root cause analysis).

What This Job Offers

• Job Type: Full-time
• Career Level: Senior