Location: Irving, TX
Salary: $69.00 USD Hourly - $74.00 USD Hourly
Description: Software Engineer (Data Engineering) - Contingent ResourceLocation: Irving, TX
About the RoleIn this contingent assignment, you will support large-scale, complex data and software engineering initiatives. You'll partner with cross-functional teams to evaluate technical challenges, design scalable solutions, and guide strategic decision-making across enterprise data platforms. This role requires strong analytical skills, a deep understanding of modern data architectures, and the ability to collaborate effectively with stakeholders at all levels.
Responsibilities- Lead and consult on complex, large-scale software engineering initiatives with broad organizational impact.
- Analyze multi-layered technical challenges requiring evaluation of diverse inputs, including ambiguous or unprecedented factors.
- Contribute to the design, development, and optimization of enterprise-class data environments.
- Apply deep knowledge of engineering standards, policies, and compliance requirements to ensure high-quality deliverables.
- Collaborate strategically with client teams, providing both technical expertise and thought leadership.
- Support data modernization, re-platforming, re-engineering, and migration efforts.
- Participate in architecture reviews and contribute to establishing standards and automation patterns for modern data platforms.
Minimum Qualifications- 5+ years of software engineering experience, or equivalent through work, consulting, military service, or education.
- 3+ years of hands-on, at-scale experience with:
- Python
- Spark
- Iceberg
- Dremio or similar tools involving virtualization, federation, or semantic layers
- Cloud platforms: Google Cloud Platform, Azure
- ETL tools: Ab Initio (preferred), Informatica, DataStage
- SQL
- Relational databases such as Oracle, MS SQL, or Teradata
- Data analysis, modeling, and design (for data engineering-focused candidates)
- Proven experience supporting and tuning large-scale, enterprise data environments.
Preferred Qualifications- 5+ years working with modern Data Warehouse, Data Lake, and Data Lakehouse architectures.
- Experience providing technical leadership for enterprise data modernization efforts, including re-platforming and large-scale migrations.
- Demonstrated success designing and implementing target-state modern data platforms.
- Experience developing automation, establishing engineering standards, and advancing reusable patterns across teams.
- Hands-on experience with modern data toolsets (e.g., Python, Spark, Iceberg, Google Cloud Platform, Azure) in large-scale environments.
Technical SkillsCategory Skill Required Experience Technical ETL No 6+ years Technical PySpark No 2-4 years Technical Python No 2-4 years Technical Python Coding No 2-4 years Technical Python Libraries No 2-4 years
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