10+ Data Engineer at Austin TX or Sunnyvale CA (Locals)
Quick Overview
Job Description
Data Engineer
Austin TX or Sunnyvale CA
LOCALS ONLY
Job Description
We are looking for a data engineer with experience in the data analytics space. What we need to see is that a candidate has done data engineering for analytics teams — the full scope of what data engineering requires — and that the consumers of their work were data analysts or data scientists.
Core Professional Competencies
- Communication: Clearly communicates technical work to diverse audiences, verbally and in writing. Participates in peer reviews and team discussions with clarity and purpose.
- Documentation: Maintains clear, structured documentation of project logic, decisions, and maintenance. Contributes to team standards for reproducibility and transparency.
- Collaboration: Works effectively with cross-functional partners. Values shared ownership and ensures continuity through knowledge sharing.
- Initiative: Comfortable in ambiguity; proactively identifies issues and opportunities. Demonstrates curiosity and critical thinking.
- Attention to Detail: Delivers high-quality, consistent code and documentation that supports long-term maintainability and trust in data systems.
Data Engineering Expertise (5+ years)
- Experienced in building and maintaining data pipelines (ETL/ELT)
- Proficient with orchestration tools (e.g., Airflow, dbt, Prefect)
- Comfortable working with cloud platforms (e.g., AWS) and tools like Snowflake
- Familiar with data lake and warehouse architecture (e.g., S3 + Athena, Delta Lake)
- Strong Python skills for data manipulation (e.g., pandas, pyarrow, pyspark)
Snowflake | Is Required | 2-5 Years | |
Data Migration | Is Required | 5-10 Years | |
Database Technologies | Is Required | 5-10 Years | |
Advanced SQL | Is Required | 5-10 Years | |
Data Engineering | Is Required | 5-10 Years | |
python | Is Required | 5-10 Years |
Data Infrastructure & Management (5+ years)
- Expertise in data modeling (star/snowflake schemas, normalization, dimensional modeling)
- Skilled in maintaining data quality and integrity (data monitoring, validation, deduplication, anomaly detection)
- Familiar with version control, CI/CD practices for data workflows (e.g., Git
Skills
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