Lead AWS Data Engineer

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

Job Description:
We are seeking a Lead Data Engineer with deep AWS expertise to guide the design, development, and optimization of our enterprise-scale data pipelines and products. In this role, you will not only contribute technically but also provide leadership to a team of data engineers, partner closely with data architects, and play a key role in planning, estimating, and resourcing major data initiatives. You'll work on high-impact projects that integrate and transform large volumes of data from multiple enterprise systems into reliable, accessible, and high-quality data products that power analytics, reporting, and decision-making across the organization.

Key Responsibilities:

• Lead the end-to-end design, development, and optimization of scalable data pipelines and products on AWS, leveraging services such as S3, Glue, Redshift, Athena, EMR, and Lambda.
• Provide day-to-day technical leadership and mentorship to a team of data engineers setting coding standards, reviewing pull requests, and fostering a culture of engineering excellence.
• Partner with data architects to define target data models, integration patterns, and platform roadmaps that align with enterprise data strategy.
• Own project planning, estimation, resourcing, and sprint management for major data initiatives, ensuring on-time, on-budget delivery.
• Implement robust ELT/ETL frameworks, including orchestration (e.g., Airflow or AWS Step Functions), automated testing, and CI/CD pipelines to enable rapid, reliable deployments.
• Champion data quality, governance, and security; establish monitoring, alerting, and incident-response processes that keep data products highly available and trustworthy.
• Optimize performance and cost across storage, compute, and network layers; conduct periodic architecture reviews and tuning exercises.
• Collaborate with analytics, reporting, and business teams to translate requirements into reliable, production-ready data assets that power decision-making at scale.
• Stay current with the AWS ecosystem and industry best practices, continuously evaluating new services and technologies to enhance data platform.
• Provide clear, concise communication to stakeholders at all levels, articulating trade-offs, risks, and recommendations in business-friendly language.

Qualifications
Minimum Requirements:

• Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related discipline plus at least 8 years of hands-on data engineering experience, or demonstrated equivalency of experience and/or education
• 3+ years in a technical-lead or team-lead capacity delivering enterprise-grade solutions.
• Deep expertise in AWS data and analytics services: e.g.; S3, Glue, Redshift, Athena, EMR/Spark, Lambda, IAM, and Lake Formation.
• Proficiency in Python/PySpark or Scala for data engineering, along with advanced SQL for warehousing and analytics workloads.
• Demonstrated success designing and operating large-scale ELT/ETL pipelines, data lakes, and dimensional/columnar data warehouses.
• Experience with workflow orchestration (e.g.; Airflow, Step Functions) and modern DevOps practices CI/CD, automated testing, and infrastructure-as-code (e.g.; Terraform or CloudFormation).
• Experience with data lakehouse architecture and frameworks (e.g.; Apache Iceberg).
• Strong communication, stakeholder-management, and documentation skills; aptitude for translating business needs into technical roadmaps.

Preferred Qualifications:

• Solid understanding of data modeling, data governance, security best practices (encryption, key management), and compliance requirements.
• Experience working within similarly large, complex organizations
• Experience building integrations for enterprise back-office applications
• AWS Certified Data Analytics - Specialty or AWS Solutions Architect certification (or equivalent) preferred; experience with other cloud platforms is a plus.
• Proficiency in modern data storage formats and table management systems, with a strong understanding of Apache Iceberg for managing large-scale datasets and Parquet for efficient, columnar data storage.
• In-depth knowledge of data cataloging, metadata management, and lineage tools (AWS Glue Data Catalog, Apache Atlas, Amundsen) to bolster data discovery and governance.
• Knowledge of how machine learning models are developed, trained, and deployed, as well as the ability to design data pipelines that support these processes.

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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