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10+ Data Engineer at Austin TX or Sunnyvale CA (Locals)

ProhiresAustin, TX🇺🇸United StatesPosted 28 Jul 2026

Quick Overview

Work Type
Hybrid
Level
Mid Senior

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

  1. Communication: Clearly communicates technical work to diverse audiences, verbally and in writing. Participates in peer reviews and team discussions with clarity and purpose.
  2. Documentation: Maintains clear, structured documentation of project logic, decisions, and maintenance. Contributes to team standards for reproducibility and transparency.
  3. Collaboration: Works effectively with cross-functional partners. Values shared ownership and ensures continuity through knowledge sharing.
  4. Initiative: Comfortable in ambiguity; proactively identifies issues and opportunities. Demonstrates curiosity and critical thinking.
  5. 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)

  1. Experienced in building and maintaining data pipelines (ETL/ELT)
  2. Proficient with orchestration tools (e.g., Airflow, dbt, Prefect)
  3. Comfortable working with cloud platforms (e.g., AWS) and tools like Snowflake
  4. Familiar with data lake and warehouse architecture (e.g., S3 + Athena, Delta Lake)
  5. 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)

  1. Expertise in data modeling (star/snowflake schemas, normalization, dimensional modeling)
  2. Skilled in maintaining data quality and integrity (data monitoring, validation, deduplication, anomaly detection)
  3. Familiar with version control, CI/CD practices for data workflows (e.g., Git

Skills

SQL
AWS
ETL
Snowflake
Airflow
Git
Pandas
Python
dbt

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