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Manager, Data Engineering

Job in Oklahoma City, Oklahoma County, Oklahoma, 73116, USA
Listing for: KPMG US
Full Time position
Listed on 2026-01-15
Job specializations:
  • IT/Tech
    Data Science Manager, Data Engineer, Data Analyst
Job Description & How to Apply Below

Join to apply for the Manager, Data Engineering role at KPMG US
. KPMG is known for its culture of individual development, inclusive environment, and innovative excellence. We are currently seeking a Manager, Data Engineering to join our Digital Nexus technology organization for a hybrid work opportunity.

Responsibilities
  • Lead a team of Azure Data Lake and business intelligence engineers in designing and delivering ADL pipelines, notebooks, and interactive Power BI dashboards that clearly communicate actionable insights, and contribute strategic thought leadership to shape the firm’s business intelligence vision and standards.
  • Design and maintain scalable data pipelines using Azure Data Factory and Databricks to ingest, transform, and deliver data across medallion architecture layers; develop production‑grade ETL/ELT solutions using PySpark and SQL to produce analytics‑ready Delta Lake datasets aligned with enterprise standards.
  • Apply critical thinking and creativity to design innovative, non‑standard BI solutions that address complex and evolving business challenges; build and optimize data models to support analytics, ensuring accuracy, reliability, and efficiency.
  • Stay ahead of emerging technologies, including Generative AI and AI agents, to identify novel opportunities that improve analytics, automation, and decision‑making across the enterprise.
  • Manage and mentor direct reports, provide technical expertise and strategic guidance to peers and cross‑functional team members, set goals, participate in strategic initiatives, and foster the development of high‑performance teams.
Qualifications
  • Minimum five years of recent experience designing and building ADL pipelines and Databricks notebooks and interactive dashboards using modern BI tools (preferably Power BI); minimum two years of recent experience designing scalable data pipelines using Azure Data Factory and Azure Databricks for ingestion, transformation, and delivery of data across medallion architecture layers.
  • Bachelor’s degree from an accredited college or university is preferred; high school diploma or GED required.
  • Demonstrated analytical and problem‑solving abilities, with a creative and methodical approach to addressing complex challenges.
  • Advanced knowledge of SQL, DAX, and data modeling concepts; proven track record in defining, managing, and delivering BI projects; ability to develop resource plans and influence organizational priorities.
  • Excellent written and verbal communication skills, including the ability to present proposals and vision to executive leadership.
  • Must be authorized to work in the U.S. without the need for employment‑based visa sponsorship now or in the future; KPMG does not sponsor U.S. work visas for this opportunity.
Compensation and Benefits

We offer a competitive total rewards package, including medical, dental, vision, disability and life insurance, 401(k) plans, and a robust suite of personal well‑being benefits. Eligible employees receive Personal Time Off per fiscal year and two paid breaks annually. Additional details about compensation and benefits can be found on our KPMG Careers site.

Equal Employment Opportunity

KPMG is an equal opportunity employer. KPMG complies with all applicable federal, state and local laws regarding recruitment and hiring. All qualified applicants are considered for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, citizenship status, disability, protected veteran status, or any other category protected by applicable federal, state or local laws. For California applicants, we comply with fair‑chance laws and will consider qualified applicants with arrest and conviction records, provided duties are not adversely affected by criminal history.

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