Data Engineer Dahl Consulting - 4.8 Brooklyn Park, MN Job Details Contract $48 - $75 an hour 1 day ago Qualifications Data model design Commercial use (data warehousing systems) Cloud analytics services Data modeling Data visualization software proficiency Data Integration (Data management) Continuous Delivery (CD) implementation Spark Business intelligence report generation Git Application deployment Apache Hive SQL Spark implementation Version control systems Query execution time improvement Application support Distributed computing DevOps automation Query management BigQuery Data analytics technologies

Hadoop Full 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 - About the Role Our client, a leading organization in the retail and consumer services industry, is seeking a Data Engineer to join a high-performing data and analytics team. This role is focused on building scalable, cloud-based data solutions that enable data-driven decision-making across a large, complex enterprise environment. The ideal candidate will have strong expertise in data engineering, distributed processing technologies, and Google Cloud Platform (GCP), with a passion for developing reliable, high-quality data products. Job Description As a Data Engineer, you will design, develop, and maintain enterprise-scale data pipelines and platforms that support analytics, reporting, and operational data needs. You will work closely with architects, engineers, analysts, and business stakeholders to deliver efficient and scalable data solutions. Key Responsibilities Design, develop, test, and maintain scalable data pipelines and ETL/ELT workflows for large-volume datasets. Build and optimize distributed data processing solutions using Apache Spark and GCP Dataproc. Develop and maintain analytical datasets and data workloads within BigQuery. Create reliable batch and streaming data processing solutions using technologies such as Spark, Hadoop, and Kafka. Develop 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. Troubleshoot production data pipelines, perform root-cause analysis, and implement long-term solutions. Implement data quality controls, monitoring, alerting, and operational support processes. Apply software engineering and DevOps best practices, including source control, automated testing, CI/CD, and deployment automation. Collaborate with cross-functional teams to translate business requirements into production-ready data solutions. Participate in code reviews and contribute to engineering standards, reusable frameworks, and best practices. Qualifications Required Qualifications Hands-on experience with Google Cloud Platform (GCP) and cloud-native data services. Advanced experience with BigQuery, including SQL development, query optimization, and large-scale data processing. Hands-on experience with Apache Spark and distributed computing frameworks. Experience with GCP Dataproc, Google Cloud Storage (GCS), and cloud-based data processing environments. Experience working with Apache Hadoop, Apache Hive, and other big data technologies. Proven experience building and supporting production-grade data engineering solutions. Strong expertise in ETL/ELT design, development, and optimization. Strong SQL skills and experience processing large, complex datasets. Proficiency in Python and/or Java/Scala. Understanding of data modeling, partitioning strategies, distributed processing concepts, and common data storage formats. Experience with DevOps practices, CI/CD pipelines, Git version control, automated deployments, and production support. Strong analytical, troubleshooting, and problem-solving skills. Experience developing reporting or analytics solutions using Looker and/or Power BI. Preferred Qualifications Experience with LookML development. Experience with BigLake, Apache Iceberg, Parquet, and modern data lake architectures. Knowledge of Terraform or other Infrastructure-as-Code (IaC) tools. Experience designing and implementing Kafka-based streaming data pipelines. Experience migrating data platforms from on-premises Hadoop/Hive environments to Google Cloud Platform. Experience supporting large-scale data modernization, cloud transformation, or enterprise data platform initiatives. Familiarity with data quality frameworks, governance practices, data lineage, and metadata management. Experience contributing to reusable data engineering frameworks and platform capabilities. 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! #IT.Indeed #LI-LS1 #LI-Hybrid Apache Hadoop,Apache Hive,Apache Spark,Apache spark ecosystem,Big Data