Senior Data Engineer - Databricks and ETL

Senior Data Engineer
- Databricks and ETL

• Pay Rate: $65.75/hour, depending on experience
• Contract Length: 6 Months
• Location:
  
  Chicago, Illinois

Raise is currently hiring a Senior Data Engineer
- Databricks and ETL on behalf of our client. They’re expanding their team to meet growing needs, making this a unique opportunity to work with an industry leader. Our Client is a technology company that combines decades of industry expertise with next-generation AI technology that helps organizations reinvent how they build, operate and deliver by pairing human ingenuity with agentic systems that scale intelligence across the enterprise.

Note:

The primary pay rate is based on W2 classification; however, we will also consider applications from candidates interested in an C2C classification, where applicable.

The Senior Associate Data Engineer in this role will need to have deep expertise in modern data architectures to support our client, ABC Supply Co. In this role, you will design, build, and optimize scalable data pipelines and cloud-native data platforms.

While core data engineering, Python/SQL proficiency, and pipeline design form the foundation of this role, Databricks and ETL development serve as key secondary competencies required to drive data integration and transformation workloads across enterprise ecosystems.

• Design, develop, and maintain robust ETL/ELT data pipelines using modern distributed processing frameworks.
• Implement and optimize data processing workloads using Databricks and Spark-based architectures.
• Collaborate with cross-functional product, analytics, and engineering teams to ingest, model, and serve high-quality data.
• Ensure data pipeline reliability, performance tuning, and cost efficiency across cloud-native environments.
• Maintain high standards of code quality through comprehensive testing, version control, and CI/CD automation.

• 5+ years of hands‑on experience in data engineering, backend engineering, or platform engineering roles.
• Core Technical Stack:
  • Databricks & ETL:
    Experience building enterprise‑grade ETL pipelines and working within Databricks environments (secondary focus area).
  • Programming & Querying:
    Strong proficiency in Python, Scala, or Java, alongside advanced SQL skills for data modeling and performance optimization.
  • Big Data Frameworks:
    Hands‑on experience with distributed data processing frameworks (Apache Spark or equivalent).
  • Cloud Platforms:
    Proven experience building and operating data solutions on major cloud platforms (Azure, AWS, or GCP).
  • Data Architecture:
    Solid understanding of data warehousing, data lakes, lakehouse patterns, and analytics ecosystems.
  • Dev Ops & Tooling:
    Experience with version control (Git), CI/CD pipelines, and modern Dev Ops practices.
  • Strong problem‑solving abilities, excellent communication skills, and the capability to independently own and deliver complex technical milestones.
• Education and Certifications
• Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, Information Systems, or a related technical field (or equivalent practical experience).
• Certifications (Preferred):
• Databricks Certified Associate Developer for Apache Spark or Databricks Certified Data Engineer Professional.
• Relevant cloud certifications (e.g., AWS Certified Data Analytics, Microsoft Certified: Azure Data Engineer Associate, or Google Cloud Professional Data Engineer).

We strive to build teams that reflect the diversity of the communities we work in. We encourage all qualified applicants to apply, including people from traditionally underrepresented groups such as women, visible minorities, Indigenous peoples, people identifying as LGBTQ2SI, veterans, and people with visible/nonvisible disabilities.

We have a dedicated webpage for accommodations where you can learn more about what we offer and request accommodation: (Use the "Apply for this Job" box below)./

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