Data Tech Lead (Databricks)

Location: Hybrid in Chicago, Illinois, United States; colleagues are expected to work from their local office or onsite with clients at least three days per week.

Base salary: $139,000–$277,900 annually, with potential performance-based incentives.

Company

hirify.global is a global risk, reinsurance, capital, people, investments, and management consulting company serving clients in 130 countries.

What you will do

• Lead delivery squads of 4–8 data engineers, set technical direction, decompose work, manage sprint execution, and own delivery outcomes.
• Write code, build and debug production data pipelines, review pull requests, and solve complex data engineering problems hands-on.
• Design data models, medallion architectures, ingestion contracts, reusable patterns, and solutions supporting schema evolution, data quality, idempotency, and lineage.
• Collaborate directly with Engagement Leads and business stakeholders to translate business needs into data solutions and explain technical trade-offs.
• Establish engineering standards covering CI/CD, version control, automated testing, code review, documentation, developer experience, and operational excellence.
• Build on Databricks, Unity Catalog, Delta Lake, Spark, AWS, Azure, infrastructure-as-code, Git workflows, and pipeline orchestration tooling.

Requirements

• 5+ years of hands-on data engineering experience, including some experience leading or mentoring other engineers.
• Strong, recent, and regular proficiency in SQL, Python, and Spark.
• Experience with cloud data platforms such as Databricks, Snowflake, Synapse, or similar on AWS, Azure, or GCP; Databricks is strongly preferred.
• Demonstrated ability to lead mixed teams of employees and contractors, including setting expectations, managing performance, and building cohesion.
• Fluency with Git, CI/CD, automated testing, infrastructure-as-code, and DataOps.
• Ability to understand the business purpose behind technical work and demonstrate intellectual curiosity about the relevant domain.
• Clear communication skills for explaining technical trade-offs to business leaders and business requirements to engineers.

Nice to have

• Experience with Databricks Unity Catalog, Delta Lake, medallion architecture, and Databricks workflows.
• Experience with dbt or similar transformation frameworks.
• Familiarity with data governance patterns, including lineage, access controls, metadata management, and data quality frameworks.
• Prior experience in financial services, insurance, benefits, or consulting environments.
• Experience building document or unstructured data ingestion pipelines.
• Exposure to LLM-based tooling, AI-assisted development, or analytics engineering.

Culture & Benefits

• Hybrid work with local-office or client-site presence at least three days per week and at least one weekly anchor day for office-based teams.
• Inclusive and flexible work environment with support for workplace accommodations.
• Health and welfare benefits, tuition assistance, 401(k) savings, retirement programs, and employee assistance programs.
• Performance-based incentives may supplement base salary.