1

Trainee Databricks Data Engineer Jobs in Madison, WI

Data Engineer

Madison, WI · On-site

$115K - $138K/yr

Databricks * Preferred / NicetoHave Technologies: * Microsoft Fabric Data Factory / Azure Data ... Engineering generalist (not toolonly or reportingonly) * Comfortable working in ambiguous ...

Sr. Data Engineer

Madison, WI

$115K - $138K/yr

The ideal candidate will possess expertise in Databricks and modern data engineering tools such as Azure Data Factory, combined with hands on experience working with biological, genomic, or other ...

Sr. Data Engineer

Madison, WI · On-site

$114K - $137K/yr

The ideal candidate will possess expertise in Databricks and modern data engineering tools such as Azure Data Factory, combined with hands on experience working with biological, genomic, or other ...

Sr. Data Engineer

Madison, WI · On-site

$114K - $137K/yr

The ideal candidate will possess expertise in Databricks and modern data engineering tools such as Azure Data Factory, combined with hands on experience working with biological, genomic, or other ...

Sr. Data Engineer

Madison, WI

$114K - $137K/yr

The ideal candidate will possess expertise in Databricks and modern data engineering tools such as Azure Data Factory, combined with hands on experience working with biological, genomic, or other ...

Sr. Data Engineer

Madison, WI · On-site

$114K - $137K/yr

The ideal candidate will possess expertise in Databricks and modern data engineering tools such as Azure Data Factory, combined with hands on experience working with biological, genomic, or other ...

Sr. Data Engineer

Madison, WI

$115K - $138K/yr

The ideal candidate will possess expertise in Databricks and modern data engineering tools such as Azure Data Factory, combined with hands on experience working with biological, genomic, or other ...

Associate Data Engineer

Madison, WI · On-site

$115K - $138K/yr

... Databricks; implement best‑practice patterns for performance, security, and cost control. • ... data engineering solutions. Qualifications : Required : • Education - Bachelor's in Computer ...

Migrate legacy SSIS packages to modern Databricks solutions * Maintain and optimize existing SSIS packages and SSRS reports * Participate in data warehouse design and implementation * Implement data ...

Data Engineering: Develop scalable, welldocumented ETL/ELT pipelines using TSQL, Python, Azure Data Factory/Fabric Data Pipelines, and Databricks; implement bestpractice patterns for performance ...

The Senior Data Engineer is responsible for software development and data engineering projects ... Expert at developing complex software and data pipelines in Python, Airflow, DBT, Databricks, C# ...

Staff Data Engineer - Science

Madison, WI

$115K - $138K/yr

As a Staff Data Engineer, this extremely seasoned professional will demonstrate competence and ... Spark on Snowflake or Databricks. * Python, Scala, SQL development. * ETL data pipelines.

Azure Databricks Developer

Madison, WI · On-site

$55.50 - $68.75/hr

Madison, WI Duration: 12 Months Must have working experience in Python R Spark Azure Databricks PySpark SparkSQL Scala Azure Data Factory DevOps KeyVault Blob Storage Data Lake Delta Lake PowerShell ...

We are looking for a Data Engineering Developer to join our team. If you love data - cleaning it ... You have a deep understanding of Apache Spark, especially as part of Azure Databricks. * You are ...

Senior Business Intelligence Engineer

Madison, WI · On-site

$105K - $144K/yr

Experiencing managing data and pipelines in Databricks is highly valued. You have experience with ... or data engineering roles * Hands-on experience with Azure Databricks, including notebook ...

Senior AI Engineer

Madison, WI · On-site

$105K - $144K/yr

... and Databricks • Troubleshoot complex issues in production environments across data ... AI engineering, machine learning, or software engineering preferred • Strong proficiency in ...

next page

Showing results 1-20

Trainee Databricks Data Engineer information

See Madison, WI salary details

$44.8K

$130.7K

$178.9K

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

As of Jun 27, 2026, the average yearly pay for trainee databricks data engineer in Madison, WI is $130,706.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,400.00 and $138,500.00 per year, depending on experience, location, and employer.

Is it hard to get hired at Databricks?

Getting hired as a Databricks Data Engineer can be competitive, as it requires strong skills in Spark, cloud platforms, and data pipeline development. Candidates often need relevant experience, technical certifications, and a solid understanding of big data tools to improve their chances.

Does Databricks hire new grads?

Databricks often hires new graduates for entry-level roles such as Trainee Data Engineer positions. These roles typically require familiarity with cloud platforms, data processing tools, and programming languages like Python or SQL. Candidates should review specific job postings for qualification details and preferred skills.

How much do Databricks data engineers make?

Databricks data engineers typically earn between $90,000 and $140,000 annually, depending on experience, location, and skill level. Professionals with expertise in Spark, cloud platforms, and data pipeline development tend to command higher salaries.

What is the difference between Trainee Databricks Data Engineer vs Junior Data Engineer?

AspectTrainee Databricks Data EngineerJunior Data Engineer
Required CredentialsBasic knowledge of Databricks, SQL, and data fundamentalsDegree in Computer Science or related field, some experience with data tools
Work EnvironmentTraining programs, mentorship, entry-level projects on Databricks platformEntry-level to mid-level data teams, real-world data projects
Employer & Industry UsageTech companies, data consulting firms, startups focusing on cloud data platformsVariety of industries including finance, healthcare, retail, with data teams

The Trainee Databricks Data Engineer is an entry-level role focused on learning Databricks and data engineering fundamentals, often within training programs. In contrast, a Junior Data Engineer typically has some hands-on experience and works on real data projects. Both roles are common in tech-driven industries, but the trainee position emphasizes skill development, while the junior role involves more independent work.

Is Databricks Data Engineer in demand?

Databricks Data Engineers are in high demand due to the increasing adoption of cloud-based data platforms and big data processing. Skills in Apache Spark, cloud environments, and data pipeline development are highly sought after, leading to strong job growth in this field.
What are popular job titles related to Trainee Databricks Data Engineer jobs in Madison, WI? For Trainee Databricks Data Engineer jobs in Madison, WI, the most frequently searched job titles are:
What job categories do people searching Trainee Databricks Data Engineer jobs in Madison, WI look for? The top searched job categories for Trainee Databricks Data Engineer jobs in Madison, WI are:
What cities near Madison, WI are hiring for Trainee Databricks Data Engineer jobs? Cities near Madison, WI with the most Trainee Databricks Data Engineer job openings:
Infographic showing various Trainee Databricks Data Engineer job openings in Madison, WI as of June 2026, with employment types broken down into 98% Full Time, and 2% Part Time. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $130,706 per year, or $62.8 per hour.

Data Engineer

Vertex Group

Madison, WI • On-site

$115K - $138K/yr

Other

Posted 4 days ago


Job description

JOB Title: Data Engineer

Location: Minneapolis, MN and Madison, WI (Locals Only) HYBRID

Duration: 6 Months Contract to Hire

heavy Azure experience with that Lakehouse, Data Lake and SQL and Python experience necessary to be successful. Also must have the dbt experience as well!

Role Summary:

Senior, handson data engineering contractor to support Modern data platform delivery across Health Payer Domains. This role requires independent ownership of endtoend data pipelines using modern cloud and Lakehouse architecture. This is a hitthegroundrunning role with minimal rampup.

  1. Key Responsibilities:
  • Design, build, and operate endtoend data pipelines
  • Source ingestion transformation analyticsready datasets
  • Develop transformations and data models using SQL and Python
  • Implement automated data quality checks and validations
  • Follow Gitbased development
  • Collaborate with business/domain stakeholders on data rules and definitions
  • Ensure solutions are secure, auditable, reliable, and supportable
  • Produce clear technical documentation and operational notes
  1. Required Technologies (MustHave)

Candidates must have strong, recent handson experience with most of the following:

Languages:

  • SQL
  • Python (PySpark preferred)

Data Platforms / Storage:

  • Cloud data platforms (Azure preferred; AWS/Google Cloud Platform acceptable)
  • Azure Data Lake Storage Gen2 (ADLS Gen2) or equivalent
  • Object storage based data lakes
  • Parquet format
  • Lakehouse concepts (Iceberg and/or Delta)

Transformation & Modeling:

  • dbt (dbt Core and/or dbt Cloud)

Source Control, GitOps & CI/CD:

  • GitHub
  • Pull request based development
  • CI/CD pipelines (GitHub Actions or equivalent)

Compute (one or more):

  • Snowflake
  • Microsoft Fabric
  • Databricks
  1. Preferred / NicetoHave Technologies:
  • Microsoft Fabric Data Factory / Azure Data Factory
  • Fabric or Databricks Notebooks
  • Orchestration tools (Airflow, Dagster, or similar)
  • Healthcare / payer domain experience (Clinical, Claims, Provider)
  1. Required Experience:
  • 7+ years of handson data engineering experience
  • Proven delivery of productiongrade data pipelines
  • Experience working independently with minimal supervision
  • Strong understanding of data quality, reliability, and operational readiness
  1. Ideal Candidate Profile:
  • Senior, handson data engineer
  • Engineering generalist (not toolonly or reportingonly)
  • Comfortable working in ambiguous, fastmoving environments
  • Strong delivery and ownership mindset