Haystack
← Back to Jobs
Engineering
VS

AWS Databricks Engineer

Virtualan SoftwareChicago, IL🇺🇸United StatesPosted Sep 25, 2026

Why This Role Stands Out

This hybrid role offers a fantastic opportunity to advance your skills in AWS, Databricks, and Apache Spark, working on impactful data engineering solutions. You'll thrive here if you're a mid-senior engineer passionate about building scalable data pipelines and optimizing ETL/ELT workflows. Apply now to join a forward-thinking company and contribute to cutting-edge data projects.

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Chicago, IL, United States
Posted
22 hours ago
Unity

Job Description

AWS Databricks Engineer

Location: Chicago, IL / Remote

Job type: Full time

Job Summary

We are seeking an experienced AWS Databricks Engineer to design, develop, and maintain scalable data engineering solutions using Databricks, Apache Spark, and AWS cloud services. The ideal candidate will have strong experience in data pipelines, ETL/ELT, data lake architecture, and cloud-based data processing.

Key Responsibilities

  • Design, develop, and maintain scalable data pipelines using Databricks and Apache Spark.
  • Build and optimize ETL/ELT workflows for batch and streaming data processing.
  • Develop solutions using Databricks notebooks, Delta Lake, PySpark, and SQL.
  • Implement and manage data solutions on AWS, including S3, Glue, Lambda, EMR, Redshift, and related services.
  • Develop and maintain data lake/lakehouse architectures using Databricks and AWS.
  • Perform data ingestion from databases, APIs, files, and other enterprise data sources.
  • Implement Delta Lake features such as schema evolution, partitioning, optimization, and data versioning.
  • Monitor, troubleshoot, and optimize data pipelines for performance, reliability, and scalability.
  • Implement security, access controls, data governance, and best practices across AWS and Databricks environments.
  • Work with data architects, analysts, developers, and business stakeholders to understand requirements and deliver data solutions.
  • Implement CI/CD and deployment automation for Databricks and data engineering workloads.
  • Develop unit/integration testing and ensure data quality and pipeline reliability.

Required Skills

  • 5+ years of experience in Data Engineering.
  • Strong hands-on experience with Databricks.
  • Strong knowledge of Apache Spark and PySpark.
  • Proficiency in Python and SQL.
  • Strong experience with AWS cloud services, particularly:
    • Amazon S3
    • AWS Glue
    • AWS Lambda
    • Amazon Redshift
    • Amazon EMR
    • IAM
  • Experience with Delta Lake and Lakehouse architecture.
  • Strong understanding of ETL/ELT, data warehousing, and data lake concepts.
  • Experience developing production-grade data pipelines.
  • Experience with Git and CI/CD tools.
  • Strong troubleshooting and performance-tuning skills.

Preferred Skills

  • Experience with Databricks Workflows/Jobs and Unity Catalog.
  • Experience with AWS Step Functions or Airflow.
  • Experience with real-time/streaming technologies such as Kafka or Kinesis.
  • Knowledge of Terraform or Infrastructure as Code.
  • Experience with data governance, lineage, and security.
  • Databricks or AWS certifications are a plus.

Education

Bachelor s degree in Computer Science, Information Technology, Engineering, or a related field preferred.

Similar jobs