Data Engineer

Dow

Remote

Quick summary

Work type: Remote
Location: Midland, MI · Houston, TX · Kankakee, IL
Posted: 3 days ago

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Salary context

How this pay compares to similar roles

Similar $163k

$87k most similar roles pay here $212k

This listing doesn't post a salary. Most similar roles pay $126,800–$199,612.

Based on 240 similar postings.

Employer

About Dow

Dow is a leading global materials science company providing innovative, sustainable solutions for packaging, infrastructure, mobility, and consumer applications.

Dow currently has 2 open roles on FindRole.

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At a glance

TL;DR · Data Engineer

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Dow is seeking a Data Engineer with 2-5 years of experience to join their team in Midland, MI, Houston, TX, or Champaign, IL. This role involves designing and implementing scalable data products on Azure Databricks, focusing on performance optimization, architecture contribution, and reliability. Key responsibilities include translating complex business requirements into technical designs, optimizing PySpark jobs for high-volume data transformation, and contributing to CI/CD pipelines in Azure DevOps/Git. The ideal candidate will have expertise in PySpark, advanced data modeling, cloud orchestration tools like Azure Data Factory, and experience with diverse databases such as SQL Server, CosmosDB, and Neo4j. This position requires a strong background in distributed processing, data quality engineering, and the ability to mentor junior engineers while ensuring efficient and cost-effective solutions for mission-critical applications.

Skills

PySpark Azure Databricks Azure DevOps Git Terraform Delta Live Tables Great Expectations Power BI Tableau SQL Server CosmosDB Neo4j CI/CD Airflow Azure Data Factory

What you'll do

Translate complex business requirements into clear, robust technical designs and data models.
Design and optimize high-volume data transformation logic using PySpark for maximum efficiency.
Contribute to the design and improvement of CI/CD pipelines in Azure DevOps/Git for reliable deployments.
Connect to various source systems and manage data persistence across diverse technologies like SQL Server, Neo4j.
Implement advanced data quality frameworks to ensure reliability for mission-critical applications.

What we're looking for

Minimum of 2 years professional experience in Data Engineering or related field
Hands-on experience with Databricks Platform for at least 2 years
Proven ability to write optimized PySpark/Spark code
Expertise in advanced data modeling techniques (e.g., dimensional modeling)
Experience with cloud orchestration tools like Azure Data Factory and Databricks Workflows

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