Data Engineer - Databricks & Data Platforms

Steampunk, Inc.

McLean (VA)

On-site

USD 110,000 - 160,000

Full time

15 hours ago
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Job summary

Steampunk in McLean, Virginia, is seeking a seasoned Data Engineer to partner with clients and build enterprise-grade data platforms, pipelines and Databricks-based solutions. You will lead data migrations with performance, reliability and scalability in mind, and work across ETL, data marts, BI tools and reports.

The role requires 2–4 years of data engineering experience, strong SQL and PySpark/Python, plus AWS experience.

Qualifications

  • 2-4 years industry experience coding commercial software and solving complex problems.
  • 2-4 years direct experience in Data Engineering with Databricks, Spark, Delta Lake.
  • Relational SQL (T-SQL preferred) and data pipelines (Airflow, Databricks Workflows, Step Functions).
  • AWS cloud services: Databricks on AWS, S3, EC2, RDS (Azure equivalents acceptable).
  • Proficiency in PySpark/Python, Java/Scala is a plus; Delta Lake/ data lakehouse knowledge.
  • Experience in an Agile environment and collaborating with data scientists.

Responsibilities

  • Lead and architect migrations of data using Databricks with focus on performance, reliability, and scalability.
  • Assess and understand ETL jobs, workflows, data marts, BI tools, and reports.
  • Address inquiries concerning customization, integration, enterprise architecture and feature functionality of data products.
  • Support an Agile software development lifecycle.
  • You will contribute to the growth of our AI & Data Exploitation Practice.

Skills

Databricks
SQL
PySpark / Python
AWS
Databricks Workflows
Airflow
Delta Lake
Big data tools
Spark
Data pipelines

Tools

Databricks
Airflow
Step Functions
Databricks Workflows

Job description

Steampunk in McLean, Virginia, is seeking a seasoned Data Engineer to partner with clients and build enterprise-grade data platforms, pipelines and Databricks-based solutions. You will lead data migrations with performance, reliability and scalability in mind, and work across ETL, data marts, BI tools and reports.

The role requires 2–4 years of data engineering experience, strong SQL and PySpark/Python, plus AWS experience.

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