Senior Data Engineer — Palantir & Lakehouse Expert

Acrisure

Austin (TX)

On-site

USD 140,000 - 180,000

Full time

16 hours ago
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Benefits offered by this job

Medical Insurance
Dental Insurance
Vision Insurance
401(k) with company match
Paid time off

Job summary

Acrisure seeks a Senior Data Engineer in Austin, onsite 4 days per week, to unify data across the enterprise. You will build scalable data pipelines using Palantir Foundry, BigQuery, Databricks and a Python/Scala/Java stack.

Collaborate with product and business teams to translate KPIs into robust data solutions and mentor junior engineers. The role emphasizes end-to-end ownership, data quality, security, and production-readiness in a hybrid cloud environment with continuous improvement of

Qualifications

  • Enterprise data platform experience with large-scale pipelines
  • Strong SQL and data modeling with performance tuning
  • Cloud data platforms (GCP/Azure) and governance

Responsibilities

  • Build reusable data engineering patterns to onboard data sources
  • Design automated data management processes for quality, security and governance
  • Own major deliverables end-to-end from design to production support
  • Design and build reusable data models, pipelines, and components
  • Collaborate with Product/Stakeholders to translate KPIs into technical solutions
  • Mentor engineers and promote best practices across the team

Skills

SQL
Python
Scala/Java
Databricks
BigQuery
Airflow/dbt

Education

Bachelor's degree in Computer Science or related field

Tools

Palantir Foundry
Ontology
AIP
Databricks

Job description

Acrisure seeks a Senior Data Engineer in Austin, onsite 4 days per week, to unify data across the enterprise. You will build scalable data pipelines using Palantir Foundry, BigQuery, Databricks and a Python/Scala/Java stack.

Collaborate with product and business teams to translate KPIs into robust data solutions and mentor junior engineers. The role emphasizes end-to-end ownership, data quality, security, and production-readiness in a hybrid cloud environment with continuous improvement of

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