Location: Irving, TX
Salary: $69.00 USD Hourly - $74.00 USD Hourly
Description: Software Engineer, Data Engineering (Contingent Role)Location: Irving, TX
W2 only - No Corp to Corp or 1099
Must not need sponsorhsip
About the RoleIn this contingent assignment, you will work on complex, large-scale data engineering initiatives that directly influence technical strategy and long-term architectural direction. You will evaluate multifaceted engineering challenges, provide expert consultation to cross-functional teams, and support the design and implementation of high-impact data solutions. This role requires strong technical depth, the ability to navigate ambiguity, and the capability to partner effectively with client stakeholders.
Responsibilities- Design and develop scalable ETL/ELT workflows and data pipelines for batch and real-time data processing.
- Build reliable data pipelines that support reporting, analytics, and downstream applications using open-source frameworks and cloud-native technologies.
- Implement operational and analytical data stores leveraging Delta Lake and modern database architectures.
- Optimize data structures, storage formats, and distributed processing strategies to support performance and scalability across large datasets.
- Collaborate with architects and engineering teams to ensure alignment with the target-state data and platform architecture.
- Apply and enforce best practices for data governance, lineage, and metadata management; integrate solutions with Google Dataplex for centralized governance and quality standards.
- Develop, schedule, and operate multi-stage workflows using Apache Airflow, including authoring and maintaining production-ready DAGs.
- Troubleshoot and resolve production pipeline issues, ensuring high reliability, data quality, and system availability.
Required Technical Skills- Data Expertise: Strong understanding of data structures, modeling techniques, data lifecycle management, and distributed data patterns.
- ETL/ELT Development: Hands-on experience designing, building, and maintaining data pipelines at scale.
- PySpark: Advanced proficiency in distributed data processing and large-scale transformations.
- NetApp Iceberg: Experience implementing open table formats for analytical workloads.
- Hadoop Ecosystem: Working knowledge of HDFS, Hive, and related big-data components.
- Cloud Technologies: Experience with Google Cloud Platform services (BigQuery, Dataflow), Delta Lake, and Dataplex for governance and metadata management.
- Programming & Orchestration: Strong skills in Python, SQL, and Spark.
- Apache Airflow: Demonstrated experience building and maintaining complex Airflow DAGs for workflow orchestration.
- Database Concepts: Solid understanding of relational, distributed, and modern analytical database systems.
Qualifications- 5+ years of software engineering or data engineering experience, demonstrated through industry roles, consulting engagements, training, military service, or formal education.
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