Data Engineer Manager

Tire Rack

Indiana (PA)

On-site

USD 140,000 - 200,000

Full time

44 hours ago
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Job summary

Tire Rack seeks a Data Engineer Manager to lead a team of data engineers and advance our lakehouse architecture using Databricks and AWS. You will design scalable data pipelines, govern data quality, and partner with BI, Analytics, and IT teams to translate business needs into reliable data solutions.

This hands-on leadership role requires strong Databricks and AWS experience, cloud cost optimization, and the ability to hire and develop talent while maintaining security and governance standards.

Qualifications

  • Bachelor’s degree in Computer Science, Information Technology, IT Software Engineering, or a related field.
  • 8+ years of professional data engineering experience with progressive responsibility.
  • 3+ years in supervisory or assistant manager roles.
  • Deep knowledge of Databricks including Spark, Delta Lake, Workflows, and Unity Catalog.
  • Strong AWS architecture experience (S3, IAM, networking, compute optimization).
  • Experience leading cloud data platform modernization initiatives.
  • Proven ability to manage cross-functional stakeholders.
  • Professional data engineering or cloud certifications are a plus.

Responsibilities

  • Lead, mentor, and develop a team of Data Engineers at the I-Senior levels.
  • Drive performance management, career development, and succession planning.
  • Foster ownership, quality, collaboration, and continuous improvement.
  • Partner with HR and leadership on hiring and workforce planning.
  • Oversee data pipelines architecture using Databricks (Spark, Delta Lake, Unity Catalog).
  • Ensure scalable AWS infrastructure (S3, IAM, Glue, Lambda, VPC).
  • Guide medallion data architecture across Bronze, Silver, Gold layers.
  • Implement CI/CD and Infrastructure-as-Code (Terraform).
  • Oversee data governance, security, and compliance standards.
  • Establish SLAs, monitoring, and reliability standards.
  • Optimize platform performance and cloud cost-management.
  • Ensure data quality frameworks are maintained.
  • Lead incident management and root-cause analysis.
  • Translate business requirements into scalable data solutions.
  • Partner with BI, Analytics, Data Science, IT teams.
  • Contribute to enterprise data roadmap and modernization.
  • Evaluate new Databricks/AWS capabilities for adoption.

Skills

Databricks
AWS
Leadership
Data governance
CI/CD
Stakeholder mgmt
Cloud architecture

Education

Bachelor’s degree in CS/IT or related field

Tools

Terraform
Spark
Delta Lake
Unity Catalog

Job description

Join Tire Rack's IT team and help build and support the data platforms that power analytics, AI, and business intelligence across the organization. As the Data Engineer Manager, you'll lead a team of data engineers, oversee the design and delivery of scalable data solutions, and help advance Tire Rack's modern lakehouse architecture using Databricks and AWS. This is an opportunity to combine technical leadership, people management, and strategic planning to create reliable, secure, and cost-efficient data capabilities.

This role is ideal for an experienced data engineering leader who enjoys developing people, solving complex technical challenges, and partnering across the organization to turn business needs into scalable data solutions.

What You'll Do
  • Lead, mentor, and develop a team of Data Engineers at the I-Senior levels.
  • Drive performance management, career development, and succession planning.
  • Foster a culture of ownership, quality, collaboration, and continuous improvement.
  • Partner with HR and leadership on hiring and workforce planning.
  • Oversee the architecture and delivery of data pipelines using Databricks, including Spark, Delta Lake, and Unity Catalog.
  • Ensure scalable AWS-based infrastructure using services such as S3, IAM, Glue, Lambda, and VPC.
  • Guide implementation of a medallion architecture across Bronze, Silver, and Gold data layers.
  • Ensure proper CI/CD and Infrastructure-as-Code practices, including tools such as Terraform.
  • Oversee data governance, security, and compliance standards.
  • Establish service-level agreements, monitoring, and reliability standards.
  • Optimize platform performance and cloud cost-management strategies.
  • Ensure data quality frameworks are implemented and maintained.
  • Lead incident-management and root-cause-analysis processes.
  • Translate business requirements into scalable data solutions.
  • Partner with Business Intelligence, Analytics, Data Science, and IT teams.
  • Contribute to the enterprise data roadmap and platform modernization initiatives.
  • Evaluate emerging Databricks and AWS capabilities for potential adoption.
  • Perform additional duties as assigned to support department and company objectives.
What We're Looking For

We're looking for a hands-on data engineering leader who can guide a talented team while remaining connected to architecture, platform reliability, and delivery. You bring strong Databricks and AWS experience, sound technical judgment, and the ability to build effective partnerships across the organization.

Required Qualifications
  • Minimum of 3 years of experience as a Supervisor or Assistant Manager.
  • Minimum of 8 years of professional experience with progressive responsibility in data engineering.
  • Deep knowledge of Databricks, including Spark, Delta Lake, Workflows, and Unity Catalog.
  • Strong AWS architecture experience, including S3, IAM, networking, and compute optimization.
  • Experience leading cloud data platform modernization initiatives.
  • Proven ability to manage cross-functional stakeholders.
  • Strong leadership, communication, analytical, planning, organizational, and interpersonal skills.
  • Ability to develop team members, build relationships, and work effectively with internal and vendor partners.
  • Bachelor's degree in Computer Science, Information Technology, IT Software Engineering, or a related technical field, or equivalent work experience.
  • Professional certifications related to data engineering or cloud platforms are a plus.
Work Days

Monday through Friday. Occasional Saturdays and Sundays may be necessary.

Work Hours

Typical hours are 8:00 a.m. - 5:00 p.m. Additional hours may be necessary based on business needs.

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