Data Analytics EngineerHarnham • Austin, TX, US
Data Analytics Engineer
Harnham • Austin, TX, US
[job_card.1_day_ago]
[job_preview.job_type]
- [job_card.full_time]
[job_card.job_description]Strong hands-on experience with Python and data libraries such as pandas, Polars, or similar Advanced SQL skills, including complex joins, window functions, and query optimization Proven experience building and operating ETL pipelines using modern data tooling Experience with BI and visualization tools (e.g., Grafana, Tableau, Looker) Familiarity with workflow orchestration tools such as Airflow, Dagster, or Prefect High-level understanding of LLMs and interest in applying them to data and analytics workflows Strong ownership mindset and commitment to data quality and reliability Experience with ClickHouse or other analytical databases (e.g., Snowflake, BigQuery, Redshift) Background working with vehicle, sensor, or logistics data Prior experience in autonomous systems, robotics, or other data-intensive hardware-driven domains
About the Role
We are looking for a Data Analytics Engineer who sits at the intersection of data engineering and analytics. In this role, you will transform raw, messy data from vehicles, APIs, and operational systems into clean, reliable datasets that are trusted and widely used—from engineering teams to executive leadership.
You will own data pipelines end to end and build dashboards that surface insights, track performance, and help teams quickly identify issues.
What You'll Do
- Build and maintain ETL pipelines that ingest data from diverse internal systems into a centralized analytics warehouse
- Work with unique and high-volume datasets, including vehicle telemetry, sensor-derived signals, logistics data, and system test results
- Write efficient, well-structured SQL to model and prepare data for analysis and reporting
- Design, build, and maintain dashboards (e.g., Grafana or similar) used to monitor system performance and operational health
- Partner closely with engineering, operations, and leadership teams to understand data needs and deliver actionable datasets
- Explore internal AI- and LLM-based tools to automate analysis and uncover new insights
What You'll Need
Nice to Have
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