Senior Data Engineer

Michels Corporation; Milwaukee (WI); On-site; USD 120,000 - 155,000; Full time

Job summary

Michels Corporation seeks a Senior Data Engineer to build and operate lakehouse pipelines powering analytics, reporting, and AI. You will own end-to-end data products, mentor engineers, and help scale the team with automation and observability.

As a senior contributor on the Enterprise Intelligence team, you design patterns, improve engineering standards, and collaborate with IT leadership to deliver durable enterprise data assets.

Qualifications

• Bachelor’s degree or equivalent hands-on experience.
• 5+ years production experience in data engineering or related field.
• Experience with cloud data platforms such as Databricks, Snowflake, Microsoft Fabric, or BigQuery.
• Proficiency with SQL, Python, Spark, and modern engineering practices including CI/CD and streaming ingestion.
• Experience building observable pipelines with monitoring, lineage, and data quality controls.

Responsibilities

• Build and maintain batch, streaming, and event-driven ingestion pipelines that reliably connect enterprise source systems to the lakehouse.
• Develop transformation logic and orchestrated workflows that turn raw source data into usable, governed datasets.
• Design and optimize data assets that support analytics, operational reporting, downstream applications, and AI-ready consumption.
• Instrument pipelines and data products with validation checks, monitoring, and alerting so data and pipeline issues are detected and resolved quickly.
• Tune pipeline, storage, and compute workloads for performance, scalability, and cost efficiency.
• Establish engineering standards and reference architectures that allow a lean team to scale responsibly.
• Lead technical design reviews and mentor engineers through pairing, code review, and technical guidance.

Skills

SQL

Python

Spark

CI/CD

Data governance

Observability

Data quality

Education

Bachelor’s degree or equivalent hands-on experience

Tools

Databricks

Snowflake

Microsoft Fabric

BigQuery

Job description

Improving America’s infrastructure isn’t for the weak. It takes grit, determination, and hard work to execute high impact projects. Michels Corporation engages 10,000 people and 18,000 pieces of heavy equipment in our insatiable drive to be the best. Our work improves lives. Find out how a career as a Senior Data Engineer can change yours.

The Senior Data Engineer builds the trusted data foundation that powers analytics, reporting, operational insight, and AI across the Michels Family of Companies. As a senior individual contributor on the Enterprise Intelligence team, this person builds and operates lakehouse pipelines and reusable data products and helps shape the engineering standards that turn raw source data into valuable, durable enterprise assets. This is a hands‑on role that owns complex work from design through production support and helps a lean team scale through patterns, automation, and observability. This role mentors engineers and provides technical leadership within delivery work. This role reports to the IT Manager, Data Platform & Engineering and is a member of the Information Technology organization.

Key Responsibilities:

• Build and maintain batch, streaming, and event-driven ingestion pipelines that reliably connect enterprise source systems to the lakehouse.
• Develop transformation logic and orchestrated workflows that turn raw source data into usable, governed datasets.
• Design and optimize data assets that support analytics, operational reporting, downstream applications, and AI‑ready consumption.
• Instrument pipelines and data products with validation checks, monitoring, and alerting so data and pipeline issues are detected and resolved quickly.
• Tune pipeline, storage, and compute workloads for performance, scalability, and cost efficiency.
• Establish engineering standards and reference architectures that allow a lean team to scale responsibly.
• Lead technical design reviews and mentor engineers through pairing, code review, and technical guidance.

Qualifications:

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical field, or equivalent hands‑on experience.
• 5+ years of production experience in data engineering, data platform engineering, analytics engineering, software engineering, or a related discipline.
• Proven experience building and operating large‑scale cloud data platforms such as Databricks, Snowflake, Microsoft Fabric, or BigQuery.
• Proficiency with SQL, Python, Spark or similar distributed processing frameworks, and modern engineering practices including version control, automated testing, CI/CD, and streaming ingestion.
• Experience building reliable, observable pipelines with monitoring, lineage, and data quality controls that operate within enterprise governance, privacy, and security requirements.

AA/EOE/M/W/Vet/Disability