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Contract Databricks Data Engineer Jobs in Racine, WI

KOHLS

Senior Data Engineer

Menomonee Falls, WI · On-site

$106K - $144K/yr

Define and maintain data contracts, including service level agreements (SLAs), schema expectations ... Mentor data engineers and champion best practices for maintainable, governed and reusable data ...

Pwc

Data Strategy-Manager

Milwaukee, WI · On-site

$99K - $232K/yr

... Databricks Certified Data Engineer / Data Analyst / ML - Proven leadership in data-driven strategies - Experience in defining data governance frameworks - Understanding of modern cloud data ...

Pwc

Data Governance- Manager

Milwaukee, WI · On-site

$99K - $232K/yr

... Databricks Certified Data Engineer / Data Analyst / ML Travel Requirements Up to 80% Job Posting End Date The salary range for this position is: $99,000 - $232,000. Actual compensation within the ...

Concurrency

Data Architect

Milwaukee, WI · On-site

$62.75 - $80.75/hr

You'll work with a high-performance engineering team and report directly to the Practice Manager ... ADLS, Databricks, Fabric, Synapse, and related tooling * Define and document reference ...

Concurrency

Data Architect

Milwaukee, WI · On-site

$62.75 - $80.75/hr

You'll work with a high-performance engineering team and report directly to the Practice Manager ... ADLS, Databricks, Fabric, Synapse, and related tooling * Define and document reference ...

CYNET SYSTEMS

Data Architect

Racine, WI · On-site

$67/hr

... of experience in Databricks Architecture. * 4+ years of experience in BI platforms ... Guide engineering teams on best practices for data modeling, pipeline design, orchestration, and ...

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Contract Databricks Data Engineer information

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$41.7K

$121.6K

$166.4K

How much do contract databricks data engineer jobs pay per year?

As of Jul 8, 2026, the average yearly pay for contract databricks data engineer in Racine, WI is $121,632.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,400.00 and $128,900.00 per year, depending on experience, location, and employer.

What are some common challenges faced by contract Databricks Data Engineers when integrating data from multiple sources?

As a contract Databricks Data Engineer, you'll often encounter challenges related to integrating diverse data sources, such as on-premises databases, cloud storage, and APIs. These challenges may include handling inconsistent data formats, managing data quality, and ensuring secure data transfers. Additionally, adapting to clients' unique data architectures and optimizing ETL pipelines for performance in a cloud environment are common tasks. Collaboration with data scientists, analysts, and other engineers is critical to ensure data is both accessible and reliable for downstream analytics and machine learning.

What are Contract Databricks Data Engineers?

Contract Databricks Data Engineers are professionals hired on a temporary or project basis to design, build, and maintain data infrastructure using Databricks, a unified analytics platform. They typically work with big data tools, cloud environments, and programming languages like Python or Scala to process and analyze large datasets. Their responsibilities often include developing data pipelines, optimizing data workflows, and collaborating with data scientists and analysts to support business objectives. Because they are contractors, their roles can vary by project and organization, offering flexibility and specialized expertise.

What are the key skills and qualifications needed to thrive as a Contract Databricks Data Engineer, and why are they important?

To excel as a Contract Databricks Data Engineer, you need strong experience in data engineering, SQL, Spark, and cloud platforms, often supported by a degree in computer science or a related field. Familiarity with Databricks, Apache Spark, Python or Scala, and cloud services like AWS or Azure is typically required, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you work effectively in dynamic, project-based environments. These competencies ensure the efficient design and implementation of scalable data solutions, driving business insights and project success.
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Contract Databricks Data Engineer jobs near you
Senior Data Engineer

Senior Data Engineer

KOHLS

Menomonee Falls, WI • On-site

$106K - $144K/yr

Other

Re-posted 13 days ago

Kohl's rating

5.7

Company rating: 5.7 out of 10

Based on 1,446 frontline employees who took The Breakroom Quiz

13th of 21 rated department stores

Job description

About the Role

As Senior Data Engineer, you will lead the development and ownership of domain data products, including batch, streaming and artificial intelligence/machine learning (AI/ML) feature pipelines. You will drive design decisions that improve data reliability, performance and governance maturity while standardizing patterns that scale across teams. You will partner cross-functionally to enable analytics, ML and GenAI use cases with trusted data.

What You’ll Do

  • Design, build and maintain batch, streaming and real-time Artificial Intelligence (AI)  feature pipelines to extract data from diverse source systems and producers (Application Programming Interfaces (APIs), events, databases, files) ensuring efficient ingestion, transformation and publishing

  • Design, refine and implement scalable data models, semantic layers and data contracts to promote consistency, reuse and accessibility

  • Owns the end-to-end data product lifecycle for the domain. Define and maintain data contracts, including service level agreements (SLAs), schema expectations, quality metrics and consumer ownership, to ensure a reliable and trustworthy experience

  • Partner with cross functional teams to co-design scalable data solutions that meet business needs and clearly define the boundaries between data pipeline responsibilities and model-building activities

  • Develop automated workflows and Continuous Integration / Continuous Deployment (CI/CD) pipelines using tools such as Airflow, Apache Spark and Python to drive reliability and faster delivery

  • Implement validation, observability and evaluation frameworks that ensure accuracy, lineage and timeliness across data pipelines and large language model (LLM) outputs

  • Apply and enforce governance, privacy and compliance standards (GDPR, PCI DSS, CCPA), ensuring data security and traceability

  • Partner with cross functional teams to translate business needs into technical data solutions that scale across domains

  • Drive performance tuning, automation and adoption of AI-powered data tools to enhance data platform efficiency

  • Mentor data engineers and champion best practices for maintainable, governed and reusable data assets

  • Own cost and performance tradeoffs for domain data products and monitor compute usage, storage growth and unit cost to implement optimizations that reduce spend while meeting SLAs

  • Additional tasks may be assigned

What Skills You Have

Required

  • 4+ years designing, building and optimizing data pipelines and models in production, ideally within large-scale cloud environments

  • Proficiency in SQL and Python (or Scala) for data development, testing and automation

Preferred

  • Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering or a related field

  • Experience with Apache Spark (or equivalent) for large-scale data processing and performance optimization

  • Experience using Airflow/Cloud Composer/Dagster for orchestration, transformation and CI/CD pipelines

  • Experience with cloud warehouses/lakes (BigQuery, Redshift, Snowflake) and object storage

  • Experience designing and optimizing streaming pipelines using Kafka, Pub/Sub, spark

  • Strong understanding of dimensional modeling, normalization and schema design for analytics and GenAI integration into data products

  • Experience with data testing, lineage, monitoring and observability frameworks to ensure data integrity and reliability

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