Sr. Data Engineer (Austin)

Title: Sr. Data Engineer Duration: full time, direct hire role Location: Austin, TX (4 Days onsite a week) Technical Stack Very strong SQL Spark / PySpark Databricks Enterprise‑scale data engineering experience Interview Process 4 rounds minimum At least 1–2 panel interviews (1 hour each) Additional round may be added only for exceptional candidates (complimentary, not punitive) Team Fit Must thrive in a large matrix organization Highly collaborative; not a “solo contributor” culture Job Description: If you love turning complex, high-volume data into trusted, reusable products—this role is for you. We’re looking for a Senior Data Engineer to design and deliver modern ELT pipelines, scalable architectures, and analytics-ready datasets that accelerate engineers, analysts, and data scientists.

You’ll lead with strong engineering fundamentals, partner across teams, and help set the standards for how data is built and used. What You’ll Do Design, develop, optimize, and maintain data architecture + ELT pipelines aligned to business outcomes Architect and implement end-to-end data solutions (warehouses/lakes, pipelines, models, products) Solve complex data challenges to deliver insights and enable decision-making at scale Build data products that boost productivity for engineers, analysts, and data scientists Engineer high-quality features for modeling in close collaboration with data scientists and business partners Lead evaluation and deployment of emerging analytics engineering tools/processes Define and drive best practices, standards, and operational excellence (quality, stability, reuse, scale) Mentor junior engineers; lead design discussions and cross-functional collaboration Partner with ML engineers, BI, and solutions architects on strategic enterprise initiatives Communicate and enable teams through education plans on standards, capabilities, and processes What We’re Looking For Deep understanding of distributed computing, scalability, and data architecture Strong critical thinking and ability to tackle big data challenges end-to-end Proficiency with data warehouses/lakes and big data technologies (e.g., Spark/Databricks, Snowflake/Redshift, distributed databases) Expertise in ELT + SQL and data analysis (advanced SQL required) Modern pipeline practices and tooling (e.g., dbt, Airflow, Spark, Python and OSS data ecosystem) Strong software engineering fundamentals and tooling (Git, CI/CD, JIRA); comfort in Linux + Bash/Z shell Cloud experience building data/analytics solutions (GCP; Azure also valued) Familiarity with BI tools (e.g., Power BI, Tableau, Looker, Alteryx) Knowledge of dimensional modeling, governance concepts, and structured/unstructured data Education & Experience Needed Bachelor’s degree in Computer Science, Statistics, Engineering, or related field 7or more years of total experience in data engineering or analytics engineering Why Join Us Own high-impact, enterprise-scale data solutions that enable analytics and ML Work with modern tools and patterns—design for scale, stability, and reuse Collaborate with cross-functional leaders and help shape the data engineering roadmap Opportunity to mentor, influence standards, and elevate the data culture