REQT: Direct End Client: Senior Data Engineer @ Austin, TX Hybrid.

Senior Data Engineer
Austin, TX Hybrid
12-Month Contract

Looking for the candidates who can work without sponsership

Position Overview

We are seeking a Senior Data Engineer to design and implement enterprise data pipelines supporting analytics and reporting initiatives within a State Government agency. The selected candidate will architect scalable data solutions that integrate multiple structured and unstructured data sources. This role requires hands-on experience building ETL/ELT pipelines, optimizing database performance, and implementing cloud-native data platforms. The ideal resource will demonstrate the ability to translate analytical requirements into scalable technical solutions. Strong experience with AWS or Azure cloud data services is required. The candidate must ensure data quality, governance, and compliance standards are consistently maintained.

Key Responsibilities

• Design and implement scalable ETL/ELT pipelines to ingest, transform, and load enterprise datasets.
• Develop and optimize SQL queries to support reporting and analytics requirements.
• Architect cloud-based data solutions using AWS or Azure data services.
• Implement data validation and quality control frameworks across pipelines.
• Integrate multiple data sources including APIs, relational databases, and flat files.
• Optimize data warehouse performance through indexing and partitioning strategies.
• Collaborate with BI teams to deliver datasets aligned with reporting needs.
• Monitor pipeline performance and implement proactive error handling mechanisms.
• Document data architecture, data lineage, and transformation processes.
• Ensure compliance with security, privacy, and regulatory standards.

Required Qualifications

• Bachelor's degree in Computer Science or related discipline.
• 6+ years of data engineering experience.
• Advanced proficiency in SQL and data modeling.
• Experience building ETL/ELT pipelines using tools such as SSIS, Glue, or Data Factory.
• Hands-on experience with AWS (S3, Redshift, Glue, Lambda) or Azure data services.
• Experience implementing data governance and validation processes.
• Strong Python or PySpark development experience.
• Experience troubleshooting performance bottlenecks in data environments.
• Experience working in structured enterprise environments.
• Strong documentation and collaboration skills.

Preferred Qualifications

• Experience supporting healthcare or public sector data initiatives.
• Experience implementing machine learning-ready data platforms.
• Experience working with large-scale distributed data systems.

Behavioral & Professional Expectations

• Demonstrate strong analytical thinking when resolving data inconsistencies.
• Communicate complex data architecture concepts to non-technical stakeholders.
• Maintain disciplined documentation of pipelines and processes.
• Proactively identify optimization opportunities within existing systems.
• Collaborate effectively with analytics, security, and application teams.