Databricks Data Engineer — Lakehouse Pipelines & AI-Ready Data

Resultant; Chicago (IL); On-site; USD 110,000 - 150,000; Full time

Job summary

Resultant is a modern consulting firm that partners with clients to turn data into outcomes. We design and deliver Databricks-based data platforms for public and private sector clients across industries.

As a Data Engineer in our Databricks practice, you will design, build, and optimize scalable ETL/ELT pipelines, work with solution architects and data scientists, and translate technical tradeoffs into clear business impact.

Qualifications

• 2+ years of hands-on data engineering experience with Databricks.
• Strong PySpark and Spark SQL skills with Delta Lake fundamentals.
• Solid SQL skills across major relational platforms.
• Experience with at least one major cloud platform (Azure/AWS/GCP).
• Excellent communication and client-facing collaboration.
• Knowledge of data modeling and ETL/ELT design principles.

Responsibilities

• Design, build, and optimize scalable ETL/ELT pipelines on Databricks.
• Implement Medallion architecture with data quality checks and schema evolution.
• Build pipelines with Delta Live Tables and handle streaming data.
• Orchestrate workloads using Databricks Workflows and integrations.
• Configure Unity Catalog for data governance and access controls.
• Collaborate with data scientists to prepare ML-ready datasets.
• Contribute to CI/CD pipelines for Databricks assets.
• Interact with clients to gather requirements and explain tradeoffs.

Skills

PySpark

Spark SQL

Delta Lake

SQL

Databricks

Cloud platforms

ETL/ELT design

Data modeling

CI/CD tooling

Airflow

Education

Bachelor's degree in Computer Science, Engineering, Data Science

Tools

Airflow

Azure Data Factory

GitHub Actions

Job description

Resultant is a modern consulting firm that partners with clients to turn data into outcomes. We design and deliver Databricks-based data platforms for public and private sector clients across industries.

As a Data Engineer in our Databricks practice, you will design, build, and optimize scalable ETL/ELT pipelines, work with solution architects and data scientists, and translate technical tradeoffs into clear business impact.