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Sr. Manager, Data Foundations

Chamberlain Group
Oak Brook, USA
Full-time
Senior · 5+ years experience
Onsite
Discovered 2 weeks ago
azuredatabricksdelta-lakegitsparksql

Full Job Posting

Minimum Qualifications

  • Education/Certifications:
  • Bachelor's Degree in computer science or equivalent relevant work experience.
  • 5+ years of experience in data engineering or analytics engineering, including 2+ years of hands-on delivery on Databricks
  • Demonstrated experience leading technical teams, whether as a people manager or as a technical lead — including setting technical direction, reviewing others' work, and developing engineers
  • Recent hands-on delivery experience building and operating production data pipelines and data models on the Databricks platform
  • Experience working alongside external delivery partners, contractors, or offshore teams, with an understanding of what it takes to get quality, predictable delivery from resources you do not directly employ
  • Demonstrated hands-on use of AI development tools such as Claude, GitHub Copilot, or Databricks Genie Code to improve the speed and quality of data engineering or analytics work, and a track record of raising adoption of those tools across a team
  • Experience partnering with stakeholders and working with highly technical developers and analysts, with an ability to earn trust
  • Significant hands-on depth in Databricks, including Delta Lake, Unity Catalog, medallion architecture, PySpark and Spark SQL, and Lakeflow Jobs orchestration — sufficient to review others' code, challenge a proposed design, and personally debug a failing production pipeline
  • Working knowledge of Databricks platform administration, including Unity Catalog structure and permissions, compute configuration, and consumption cost management
  • Advanced SQL and demonstrated data modeling skill, including dimensional modeling and design of curated, consumption-ready data products
  • Working knowledge of the analytics consumption layer — governed semantic and metric definitions, dashboards, and natural language or AI agent access to data — sufficient to set standards for it and review the team's work
  • Working knowledge of CI/CD and pipeline-as-code practices for data, including Git-based workflows, automated testing, and promotion across environments
  • Practical understanding of data quality, observability, and data privacy controls, and how to embed them into delivery rather than bolt them on
  • Ability to operate as a player/coach — setting technical direction and reviewing others' work while remaining credible and capable in the code
  • Sound judgment about where AI tooling meaningfully accelerates delivery and where it introduces risk, with the discipline to hold AI-assisted work to the same review, testing, and security standards as any other change
  • Ability to deal with ambiguity and make quality decisions in a dynamic, fast-paced environment
  • Strong presentation, written and verbal communication skills with an ability to communicate effectively to all levels of the organization
  • Insistence on high standards with a strong desire to transform and improve and a bias for action
  • Ability to travel up to 5%
  • Experience directly managing the delivery and performance of external partner, systems integrator, or offshore teams, including work allocation, acceptance of deliverables, and holding partners to agreed quality and throughput
  • Experience leading both data engineering and analytics engineering disciplines, with clear ownership boundaries between ingestion and the curated and semantic layers
  • Experience establishing reusable, version-controlled transformation frameworks with automated testing and documentation built in
  • Experience applying agentic AI development tools, such as Claude Code or comparable tools, to data engineering work including legacy code migration, test generation, and large-scale refactoring
  • Experience defining team-level standards or enablement for responsible AI tool use in an engineering organization
  • Experience with streaming and near real-time ingestion patterns, including Spark Structured Streaming and Auto Loader
  • Experience migrating or modernizing legacy ETL onto a lakehouse architecture
  • Experience with agile/scrum development methodologies
  • Azure platform expertise, including one or more certifications
  • Familiarity with Lakeflow Declarative Pipelines (formerly Delta Live Tables)
  • Familiarity with Declarative Automation Bundles (formerly Databricks Asset Bundles) or comparable deployment tooling
  • Experience enabling self-service analytics through governed semantic models and curated, well-documented data products
  • Familiarity with data catalog, master data management, and data quality tooling
  • The pay range for this position is $129,700.00 - $226,900.00; base pay offered may vary depending on a number of factors including, but not limited to, the position offered, location, education, training, and/or experience. In addition to base pay, also offered is a comprehensive benefits package and 401k contribution (all benefits are subject to eligibility requirements). This position is eligible for participation in a short-term incentive plan subject to the terms of the applicable plans and policies.
  • Chamberlain Group wants all of its employees to succeed and encourages people of all backgrounds to apply. We’re proud to be an Equal Opportunity Employer, and you’ll be considered for this role regardless of race, color, religion, sex, national origin, age, sexual orientation, ancestry; marital, disabled or veteran status. We’re committed to fostering an environment where people of all lived experiences feel welcome.
  • Persons with disabilities who anticipate needing accommodations for any part of the application process may contact, in confidence [email protected].
  • NOTE: Staffing agencies, headhunters, recruiters, and/or placement agencies, please do not contact our hiring managers directly.

Experience:

  • Knowledge, Skills, and Abilities:
  • Other:

Preferred Qualifications

  • Education/Certifications:
  • Databricks Certified Data Engineer Associate or Professional
  • Azure platform certification (e.g., Azure Data Engineer Associate)

Experience:

  • #LI-Hybrid
  • #LI-JM2

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