Technology

Data Engineer

Dahl ConsultingBrooklyn Park, MN🇺🇸United StatesPosted Oct 9, 2026

Why This Role Stands Out

This hybrid Data Engineer role offers a fantastic opportunity to contribute to significant data modernization initiatives within a leading retail enterprise, leveraging your skills in cloud platforms and distributed processing. You'll thrive here if you're a mid-senior level professional eager to build scalable data solutions and collaborate with cross-functional teams, with a competitive hourly rate of $48-$75. Apply now to make a tangible impact and advance your career in a dynamic environment.

Quick Overview

Salary

$48 - $75/hr

Seniority

Mid Senior

Work mode

Hybrid

Location

Brooklyn Park, MN, United States

Posted

6 days ago

GCPSQLScalaETLLookerApacheApache SparkBigQueryGitGoogle CloudHadoopHiveJavaKafkaPythonTerraform

Job Description

Title: Data Engineer
Location: Brooklyn Park, MN | Hybrid
Job Type: Contract (6 months)
Compensation: $48.00 - $75.00 per hour (W2)
Industry: Retail
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About the Role
Our client, a leading enterprise in the retail and consumer services industry, is seeking a Data Engineer to support large-scale data modernization and analytics initiatives. This role will focus on designing and building scalable data platforms, developing high-performance data pipelines, and delivering reliable data solutions that support business intelligence, operational reporting, and advanced analytics.
The ideal candidate will have strong experience with cloud-based data engineering, distributed processing frameworks, and DevOps practices, with a focus on Google Cloud Platform (GCP) technologies.

Job Description
As a Data Engineer, you will be responsible for designing, developing, and maintaining robust data solutions that process and transform large volumes of data across enterprise systems. You will work closely with architects, platform engineers, application teams, and business stakeholders to deliver scalable and reliable data products.
Key Responsibilities

Design, develop, test, and maintain scalable data pipelines and ETL/ELT workflows for high-volume datasets.
Build and optimize distributed data processing solutions using Apache Spark and GCP Dataproc.
Develop and maintain analytical datasets and processing workloads in BigQuery.
Create reliable batch and streaming data solutions using technologies such as Spark, Hadoop, and Kafka.
Design and support data ingestion and transformation pipelines across source systems, data lakes, and analytics platforms.
Optimize Spark and BigQuery workloads for performance, scalability, reliability, and cost efficiency.
Investigate and resolve production issues through troubleshooting, root-cause analysis, and implementation of long-term solutions.
Implement data quality controls, monitoring, logging, alerting, and operational processes.
Apply software engineering and DevOps best practices, including source control, CI/CD pipelines, automated testing, and deployment automation.
Collaborate with cross-functional teams to translate business requirements into scalable data solutions.
Participate in code reviews and contribute to reusable frameworks, standards, and engineering best practices.

Qualifications
Required Qualifications

Proven experience in Data Engineering with a strong track record of building and supporting production-grade data pipelines.
Hands-on experience designing and developing ETL/ELT solutions.
Experience working with Google Cloud Platform (GCP).
Strong expertise with BigQuery, including SQL development, performance tuning, and query optimization.
Hands-on experience with Apache Spark and distributed data processing frameworks.
Experience with GCP Dataproc.
Knowledge of Hadoop, Hive, Kafka, and the Apache Spark ecosystem.
Strong SQL skills and experience processing and analyzing large datasets.
Proficiency in Python and/or Java/Scala.
Understanding of data modeling, partitioning strategies, distributed computing concepts, and common data storage formats.
Experience with DevOps practices, including Git, CI/CD, automated deployments, and production support.
Strong analytical, troubleshooting, and problem-solving skills.

Preferred Qualifications

Experience with Looker and/or LookML.
Experience working with Google Cloud Storage (GCS), BigLake, Hive, Apache Iceberg, and Parquet.
Experience with Infrastructure as Code (IaC) tools such as Terraform.
Experience building and supporting Kafka-based streaming pipelines.
Experience migrating data platforms or workloads from on-premises Hadoop/Hive environments to GCP.
Experience supporting large-scale data lake, cloud migration, or data platform modernization initiatives.
Familiarity with data governance, data quality, lineage, metadata management, and related best practices.

Benefits
Dahl Consulting is proud to offer a comprehensive benefits package to eligible employees that will allow you to choose the best coverage to meet your family’s needs. For details, please review the DAHL Benefits Summary: https://www.dahlconsulting.com/benefits-w2fta/.

How to Apply
Take the first step on your new career path! To submit yourself for consideration for this role, simply click the apply button and complete our mobile-friendly online application. Once we’ve reviewed your application details, a recruiter will reach out to you with next steps!

Equal Opportunity Statement
As an equal opportunity employer, Dahl Consulting welcomes candidates of all backgrounds and experiences to apply. If this position sounds like the right opportunity for you, we encourage you to take the next step and connect with us. We look forward to meeting you!