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PulteGroup

Lead Data Engineer

Posted 17 Days Ago
In-Office
2 Locations
Senior level
In-Office
2 Locations
Senior level
The Lead Data Engineer is responsible for architecting and optimizing data solutions, mentoring junior engineers, and leading migration to Microsoft Fabric.
The summary above was generated by AI

Build a Career That Builds Your Future — with PulteGroup! 

Welcome to PulteGroup where we believe in building more than just homes—we believe in building inspired employees, meaningful careers, and a legacy of excellence. If you're looking for work that moves you, a team that values your ideas, and a company that brings you pride, you’ve come to the right place. 

As one of the nation’s largest and most respected homebuilders, PulteGroup offers opportunities to grow within a Fortune 500 company that’s consistently recognized as a Fortune 100 Best Company to Work For and a certified Great Place to Work. We’re driven by the bold purpose of Building Incredible Places for People to Live Their Dreams.   

For over 70 years, we’ve been building more than homes—we’ve been building trust, innovation, and a culture where every team member is empowered to thrive. Join a company that champions inclusion, celebrates diversity, and supports your personal and professional journey. 

Headquartered in vibrant Atlanta, Georgia, and operating in over 45 markets nationwide, we’re proud to build homes through our trusted family of brands—including Innovative Construction Group, Centex, Pulte Homes, Del Webb, DiVosta Homes, American West, and John Wieland Homes and Neighborhoods, Pulte Mortgage, PGP Title, Pulte Insurance Agency —all united under the PulteGroup name. 

Apply now and discover a career where your contributions are valued, your growth is supported, and your work makes a lasting impact

Job Summary:

The Lead Data Engineer is a senior technical leader responsible for architecting, building, and optimizing enterprise-scale data solutions that enable advanced analytics and business insights. This role combines deep technical expertise with leadership skills to guide the data engineering team and ensure alignment with organizational goals. The Lead Data Engineer will drive the modernization of the data platform, including the transition to Microsoft Fabric, while providing scalability, security, and compliance.

Primary Job Responsibilities

Leadership & Strategy

  • Mentor and coach junior data engineers; foster a culture of collaboration and continuous improvement.
  • Define and implement the organization’s data engineering strategy, aligning with business objectives and future growth.
  • Represent the data engineering team in executive discussions and provide strategic guidance on data initiatives.

Data Platform Design & Optimization

  • Own the architecture and performance of the enterprise data platform, ensuring reliability and scalability.
  • Lead the design and implementation of complex data pipelines, ETL/ELT processes, and integration strategies.
  • Drive adoption of DataOps practices and automation for efficient data delivery.

Modernization & Migration

  • Lead the migration from legacy systems to Microsoft Fabric, ensuring seamless integration and minimal disruption.
  • Evaluate emerging technologies and recommend solutions that enhance data capabilities and cost efficiency.

Collaboration & Governance

  • Partner with business stakeholders, data scientists, and analysts to deliver data solutions that meet business needs.
  • Ensure data quality, security, and compliance with regulatory standards.
  • Maintain clear documentation for data processes, models, and tools.

Operational Excellence

  • Monitor and optimize database performance; troubleshoot and resolve complex data issues.
  • Provide escalation support for critical production issues, including after-hours when necessary.

Career Level (P4)

Organizational Impact:

  • Works to achieve day-to-day objectives with major impact on the area of responsibility.
  • Contributes to the development of goals the area and planning efforts (budgets, operational plans, etc.).
  • Manages large projects or processes with moderate impact on the achievement of sub-family results.
  • Work is performed with limited oversight.
  • Typically responsible for coaching, reviewing and delegating work to lower-level professionals.
  • Provides measurable input to new products, processes or standards in operational plans in order to implement operational objectives.

Leadership & Talent Management: 

  • Typically, responsible for providing guidance, coaching and training to other employees within job area.
  • Typically, responsible for managing major/complex projects at this level, involving delegation of work and review of work products.
  • Additional responsibilities for this role:
    • Recruits, selects, coaches, and develops team members.
    • When direct reports are assigned, conducts performance reviews per HR guidelines. Takes corrective actions, including Performance Improvement Plans and terminations, when necessary.  Also manages professional growth and development plans.

Knowledge & Experience:  

  • Requires deep knowledge of area typically obtained through higher education combined with experience.
  • Typically viewed as a subject matter expert within discipline. May have broad knowledge of project or program management.
  • Typically requires a university degree or equivalent experience and minimum 6-8 years of prior relevant experience.

Required Skills

Technical Expertise

  • Advanced proficiency in Python for data pipeline development and orchestration
  • Advanced proficiency in SQL for data transformation and performance tuning 
  • Strong understanding of Microsoft Fabric architecture and components: Data Lake, Azure Data Factory, PowerBI
  • Experience with PySpark and Databricks a plus 
  • Hands-on experience in data warehousing, data lakes, data modeling and ETL/ELT methodologies
  • Experience with Data Vault data modeling a plus
  • Proficiency in KQL is a plus

Leadership & Communication

  • Proven ability to lead technical teams and mentor junior engineers.
  • Strong collaboration skills to work across IT and business teams.

Best Practices & Compliance

  • Expertise in data governance, security, and compliance frameworks.
  • Knowledge of DevOps principles and CI/CD for data solutions.

Preferred

  • Experience with real-time data processing and big data technologies.
  • Understanding of advanced analytics and AI/ML integration within data platforms.

Required Licensing, Registration and/or Certifications

  • Not applicable

Physical Requirements:

  • May require travel

PulteGroup, Inc. and its affiliates do not accept unsolicited resumes from individual recruiters or third party recruiting agencies (collectively, “Recruiters”) in response to job postings. If Recruiters nevertheless submit one or more unsolicited resumes to any employee at PulteGroup, Inc. or its affiliates without a valid written agreement in place for this position, it will be deemed the sole property of PulteGroup, Inc. and its affiliates. No fee will be owing or paid to Recruiters who submit unsolicited candidates, in the event the candidate is hired by PulteGroup, Inc. or its affiliates as a result of the referral, without a written agreement between PulteGroup, Inc. and through any means other than via our Applicant Tracking System.

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by law. We will provide a reasonable accommodation to a qualified applicant with a disability that will enable the individual to have an equal opportunity to participate in the application process and to be considered for a job.

This Organization Participates in e-Verify

Pulte Homes of Minnesota is an equal employment opportunity/affirmative action employer.

California Privacy Policy

Top Skills

Azure Data Factory
Data Lake
Data Vault
Databricks
Kql
Microsoft Fabric
Power BI
Pyspark
Python
SQL

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