Job Details

Title: Lead Data Engineer (AWS Lakehouse)
Location: Dallas, TX or Houston, TX (hybrid)
Duration: Direct Hire
Work Requirements: US Citizen, GC Holders or Authorized to Work in the U.S.

Job Description:
We're hiring a hands-on Lead Data Engineer to help modernize an enterprise data platform from legacy, on-prem systems to a cloud-native AWS lakehouse. This is a lead individual contributor role with high ownership and a strong hands-on focus (approximately 70%), balancing deep technical delivery with design guidance, code reviews, and mentorship.

While we leverage AWS S3 Tables (managed Apache Iceberg), success in this role requires a solid understanding of how modern table formats operate under the hood, beyond reliance on fully managed tooling.

This position will offer flexibility for hybrid work schedules to include both in-office presence and telecommute/virtual work, to be based from either Houston or Dallas, TX.

Key Responsibilities:

• Design, build, and operate end-to-end, production-grade data pipelines in AWS
• Re-engineer legacy ETL into a lakehouse architecture (Bronze/Silver/Gold) on S3
• Work hands-on with open table formats in AWS (S3 Tables / Apache Iceberg) and understand their metadata, snapshots, schema evolution, and performance characteristics
• Develop pipelines using Python, PySpark, and Spark on AWS Glue and/or EMR
• Orchestrate workloads using Airflow or AWS Step Functions
• Partner with data architects to translate business requirements into data products
• Perform code reviews, mentor engineers, and contribute hands-on in production
• Support agile development practices, including planning, demos, and reviews

Qualifications

Minimum Requirements:

• BA/BS in Computer Science, Engineering, or a related field plus at least 8 years of hands-on data engineering experience, or demonstrated equivalent experience and education
• Strong, current hands-on experience with AWS data services, including S3 and Spark-based processing
• Hands-on experience with an open table format (such as Apache Iceberg, Delta Lake, or Hudi), with a clear understanding of table metadata, schema evolution, partitioning, and performance tradeoffs
• Proficiency in Python and PySpark for production data pipelines
• Experience designing, building, and operating data pipelines end-to-end in AWS
• Experience orchestrating data pipelines using Airflow or AWS Step Functions
• Strong communication skills and ability to operate as a hands-on technical lead

Preferred Qualifications:

• Master's degree in a relevant field
• Experience working with AWS S3 Tables or native Apache Iceberg in AWS environments
• Experience modernizing on-prem or legacy data warehouse platforms
• Familiarity with lakehouse performance tuning, schema evolution, and partitioning
• Experience with data pipeline orchestration frameworks
• Exposure to AI/ML data readiness or downstream analytics use cases
• Experience working in large, complex enterprise environments

Why You'll Love Working Here:

• Leadership Impact: Shape the direction of our enterprise data platform and mentor the next generation of data engineers
• Enterprise Reach: Work with diverse, large-scale datasets from critical business systems.
• Modern Tech Stack: AWS-first environment with continuous improvement and best-practice adoption.
• Career Growth: Opportunities to advance into architecture or senior leadership roles.

About INSPYR Solutions
Technology is our focus and quality is our commitment. As a national expert in delivering flexible technology and talent solutions, we strategically align industry and technical expertise with our clients' business objectives and cultural needs. Our solutions are tailored to each client and include a wide variety of professional services, project, and talent solutions. By always striving for excellence and focusing on the human aspect of our business, we work seamlessly with our talent and clients to match the right solutions to the right opportunities. Learn more about us at inspyrsolutions.com.

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