Recently postedRemoteTechnology

Data Engineer

Dahl ConsultingUnited States🇺🇸United States

Quick overview

Salary$67 - $83/hr

SeniorityMid Senior

Work modeRemote

LocationUnited States

SQLScalaGitApache SparkETLLookerApacheBigQueryGoogle CloudHadoopHiveJavaKafkaPythonTerraformCI/CD

Job description

Title: Data Engineer
Location: Remote
Job Type: Contract (6 months)
Compensation: $67.00 - $83.00 per hour (W2)
Industry: Retail
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About the Role
Our firm is seeking a Data Engineer on behalf of a leading national retail organization that leverages advanced cloud technologies, big data platforms, and analytics to drive business decisions across a large-scale enterprise environment. This role will focus on designing and building scalable data solutions that support high-volume data processing, reporting, and analytics initiatives. The ideal candidate is passionate about modern data engineering practices, cloud-based architectures, and delivering reliable, production-grade data pipelines.

Job Description
As a Data Engineer, you will be responsible for developing, optimizing, and supporting large-scale data ecosystems that power critical business functions. You will collaborate with cross-functional teams to design and implement scalable data solutions using modern cloud and big data technologies.
Key Responsibilities

Design, develop, test, and maintain scalable ETL/ELT pipelines for high-volume datasets.
Build and optimize distributed data processing solutions using Apache Spark and Google Cloud Dataproc.
Develop and maintain analytical datasets and data processing workloads within BigQuery.
Create reliable batch and streaming data processing solutions utilizing technologies such as Spark, Hadoop, and Kafka.
Design and implement data ingestion and transformation pipelines across source systems, data lakes, and analytical platforms.
Optimize Spark and BigQuery workloads for performance, scalability, reliability, and cost efficiency.
Monitor, troubleshoot, and support production data pipelines, performing root-cause analysis and implementing long-term solutions.
Implement data quality frameworks, monitoring, logging, alerting, and operational controls.
Apply software engineering and DevOps best practices, including source control, automated testing, CI/CD, and deployment automation.
Partner with architects, platform engineers, application teams, and business stakeholders to gather requirements and deliver enterprise-grade data solutions.
Participate in code reviews and contribute to reusable frameworks, standards, and engineering best practices.

Qualifications
Required Qualifications

Strong hands-on experience in Data Engineering with a proven track record of building production-grade data pipelines.
Expertise in ETL/ELT development methodologies and data integration processes.
Hands-on experience with Google Cloud Platform (Google Cloud Platform).
Strong experience with BigQuery, including SQL development, query optimization, and performance tuning.
Experience developing distributed data processing applications using Apache Spark.
Experience with Google Cloud Platform Dataproc.
Experience working with Hadoop ecosystems, including Apache Hadoop and Apache Hive.
Experience with Apache Kafka or other streaming technologies.
Strong SQL skills and experience processing large-scale datasets.
Proficiency in Python and/or Java/Scala.
Understanding of data modeling concepts, partitioning strategies, distributed computing, and common data storage formats.
Experience with DevOps practices, Git, CI/CD pipelines, automated deployments, and production support.
Strong analytical, troubleshooting, and problem-solving abilities.

Preferred Qualifications

Experience with Looker and/or LookML.
Familiarity with Google Cloud Storage (GCS), BigLake, Apache Iceberg, Hive, and Parquet.
Experience using Terraform or other Infrastructure-as-Code (IaC) solutions.
Experience designing and supporting Kafka-based streaming architectures.
Experience migrating data platforms from on-premises Hadoop/Hive environments to Google Cloud Platform.
Background in large-scale data lake modernization or enterprise data platform transformation initiatives.
Knowledge of 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: .

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!
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