Senior Data Engineer

Stott and May; Chicago (IL); Hybrid; USD 140,000 - 170,000; Part time

Job summary

Stott and May is seeking a Senior Data Engineer in Chicago to join a growing Data & Analytics team. You will build scalable data pipelines, integrate data from enterprise systems, and move ML models into production.

The role focuses on delivering reliable, production-ready data solutions while collaborating with data scientists, analytics teams, and business stakeholders. Hybrid/Onsite in Chicago with a 6-month initial contract.

Qualifications

• 5+ years of data engineering experience.
• Proficient in Python, SQL and Snowflake.
• Experience with dbt, REST APIs, and data modeling.

Responsibilities

• Design, build, and maintain scalable data pipelines.
• Develop data models and optimize Snowflake schemas.
• Ingest data from enterprise systems via APIs.
• Automate ETL/ELT workflows across systems.
• Support ML deployment and production data ops.
• Ensure data quality, reliability, and performance.
• Collaborate with Data Science, Analytics, and business stakeholders.
• Troubleshoot production issues and improve pipelines.

Skills

Data Engineering

Python

SQL

Snowflake

dbt

ETL/ELT

REST APIs

Data Modeling

Cloud Data Platforms

Communication

Tools

dbt

Job description

Duration: 6-month initial contract with likely extension

About the Role

We're looking for a Senior Data Engineer to join a growing Data & Analytics team focused on building the data platform that powers reporting, forecasting, and AI initiatives across the business.

This role is ideal for someone who enjoys building scalable data pipelines, integrating data from multiple enterprise systems, and helping move machine learning models into production. You'll work closely with data scientists, analytics teams, and business stakeholders to deliver reliable, production-ready data solutions.

Responsibilities

• Design, build, and maintain scalable data pipelines using Python and SQL.


• Develop and optimize data models using Snowflake and dbt.


• Build integrations with APIs and enterprise applications to ingest and process data.


• Automate recurring workflows and data movement across multiple systems.


• Support the deployment, monitoring, and maintenance of machine learning models in production.


• Ensure data quality, reliability, and performance across the data platform.


• Collaborate with Data Science, Analytics, and business stakeholders to deliver data solutions that support operational and strategic decision-making.


• Troubleshoot production issues and continuously improve existing pipelines and processes.

Required Skills

• 5+ years of Data Engineering experience.


• Strong Python and SQL development skills.


• Hands-on experience with Snowflake.


• Experience building data transformations using dbt.


• Experience developing and maintaining ETL/ELT pipelines.


• Experience integrating with REST APIs or other enterprise systems.


• Strong understanding of data modeling and cloud data platforms.


• Excellent communication skills and ability to work with technical and non-technical stakeholders.

Nice to Have

• Experience supporting MLOps or deploying machine learning models into production.


• Experience in manufacturing, industrial, or supply chain environments.


• Familiarity with workflow orchestration and automation tools.


• Location: Chicago, IL (Hybrid/Onsite)


• Duration: 6-month initial contract with likely extension