Data Engineering Manager (Azure Databricks)

Location: Chicago, Illinois; hybrid. Candidates must be authorized to work in the United States without employer sponsorship now or in the future.

Target salary: $165,000–$185,000 annually for roles located in Illinois, plus bonus eligibility and comprehensive benefits.

Company

hirify.global is a law and professional services firm.

What you will do

• Lead, mentor, and develop a scrum team of 5–7 data engineers through one-on-ones, performance reviews, and career development.
• Set technical direction, coding standards, design patterns, and engineering best practices for the enterprise Databricks data platform.
• Design and evolve the Bronze/Silver/Gold Lakehouse architecture on Azure Databricks using Delta Lake, Apache Spark, and ADLS Gen2.
• Oversee scalable ETL and streaming pipelines, reusable metadata-driven ingestion frameworks, and modular data transformations.
• Establish data quality, validation, monitoring, alerting, testing, and SLA practices across pipelines and data products.
• Collaborate with the Data Architect, analytics, and business teams while troubleshooting complex platform, infrastructure, and pipeline issues.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
• At least 5 years of hands-on data engineering experience and at least 2 years managing or leading data engineers with direct people-management responsibilities.
• Strong expertise in Azure Databricks or similar platforms, Delta Lake, Databricks SQL, Apache Spark, Unity Catalog, and Databricks Workflows.
• Proficiency in Python and SQL, with experience in Lakehouse architecture, schema evolution, data modeling, and large-scale data processing.
• Experience with CI/CD, version control, automated testing, monitoring, code reviews, engineering standards, and data quality practices.
• Strong communication, stakeholder management, organizational, decision-making, and prioritization skills.

Nice to have

• Master’s degree in Computer Science, Engineering, or a related field.
• Experience with Azure DevOps, ADLS Gen2, Azure Key Vault, Infrastructure as Code, and Governance as Code.
• Familiarity with enterprise data governance, metadata management tools, machine learning workloads, and feature engineering in a Lakehouse environment.
• Experience leading agile or scrum data engineering teams and working in legal or professional services.

Culture & Benefits

• Hybrid work arrangement.
• Bonus eligibility and a comprehensive benefits program.
• Focus on technical excellence, collaboration, continuous improvement, confidentiality, discretion, and high-quality delivery.