Lead Data Engineer
Job Title: Lead Data Engineer
Industry: Transportation / Technology
Location: Chicago, IL (Hybrid Preferred | Remote Considered)
Assignment Type: Contract-to-Hire
Pay: $75.00 - $85.00 / Per Hour | $130,000 – $150,000 / Annually + Bonus upon conversion
Work Schedule: Hybrid schedule (3 days onsite preferred). Remote candidates with strong qualifications will also be considered.
Benefits: This position is eligible for medical, dental, vision, and 401(k).
About The Company:
Our client is a well-established organization undergoing a major transformation of its enterprise data environment. They are investing in modern cloud technologies and building a scalable analytics platform to support future business growth. This is an opportunity to join a collaborative team where you'll have significant influence over data strategy, architecture, and engineering best practices.
Job Description:
Our client is seeking an experienced Lead Data Engineer to help design, build, and enhance enterprise data solutions. This individual will lead the development of scalable cloud-based data pipelines, work closely with business stakeholders to deliver impactful analytics solutions, and provide technical leadership across the data engineering team. The ideal candidate is passionate about modern data platforms, enjoys solving complex technical challenges, and thrives in a collaborative Agile environment.
Key Responsibilities:
- Design, develop, and support scalable ETL/ELT pipelines for enterprise reporting and analytics.
- Build cloud-based data solutions utilizing Databricks and AWS technologies.
- Create reliable, high-performing data workflows that support both batch and streaming processes.
- Collaborate with business partners to understand reporting and data requirements.
- Establish and promote engineering standards, coding best practices, and data governance.
- Optimize existing data architecture for performance, scalability, and reliability.
- Mentor junior team members and provide technical leadership on complex initiatives.
- Troubleshoot production issues and drive continuous improvements across the data platform.
Qualifications:
Required:
- 10+ years of experience in data engineering or a related field.
- Hands-on experience with Databricks, including Spark and Delta Lake.
- Strong ETL development experience, including SSIS.
- Advanced SQL and Python programming skills.
- Experience working within AWS cloud environments.
- Oracle database experience.
- Knowledge of Agile development methodologies.
- Strong communication and collaboration skills.
Preferred:
- Experience designing enterprise data architecture.
- Familiarity with modern Lakehouse concepts and cloud data platforms.
- Experience with CI/CD and DevOps practices.
- Previous technical leadership or mentoring experience.
- Transportation, logistics, or fleet management industry experience is a plus.
Additional Details:
- Contract-to-hire opportunity.
- Team size of approximately 10 engineers.
- Two-step interview process consisting of a technical interview followed by a behavioral interview.
- Candidates must not have previously applied or been submitted for this opportunity.
- Upon a conditional offer of employment, the position requires a background check.
Perks:
- Opportunity to help shape a modern enterprise data platform.
- High-visibility role with strong technical ownership.
- Collaborative engineering culture with opportunities to mentor others.
- Exposure to modern technologies including Databricks, AWS, SQL, Python, and cloud data architecture.
- Long-term career growth with potential for permanent employment and bonus eligibility.
Addison Group is an Equal Opportunity Employer. Addison Group provides equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, gender, sexual orientation, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran, in accordance with applicable federal, state, and local laws. Reasonable accommodation is available for qualified individuals with disabilities upon request.
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