Role: Senior Data Engineer

Type: Contract (C2C)

Location & Onsite: Blue Ash, OH (5 days onsite)

Client Name: Kroger

Visa: Any visa acceptable

Interview Process: In-person onsite

Team Details: 10 team members; work independently with peer programming sessions throughout the day

Top Skills: Azure Databricks, Python, Spark

Soft Skills: Problem-solving, attention to detail, ability to work independently and collaboratively in an agile team

VERY IMPORTANT DETAILS:

• Work location must be local
• Interviews will be in person, onsite
• Candidates must be willing to come onsite for their interview and work fully onsite with the team
• Prescreening includes 3 video questions; candidates must answer using their own knowledge and experience, no AI-generated responses
• Include a link to the candidate's LinkedIn profile with the submittal

Requirements:

• Senior experience as a Data Engineer
• Strong experience with Azure Databricks, Spark, Python
• Strong SQL skills and database experience
• Experience monitoring and optimizing Databricks clusters or workflows
• Experience working with Azure data services and integrating them with Databricks and enterprise data platforms
• Experience building and optimizing distributed data processing systems (partitions, joins, shuffles, cluster performance)
• Experience with data pipeline development using tools such as Delta Live Tables (DLT) or Databricks SQL
• Experience with orchestration, messaging services, or serverless components (e.g., Azure Functions)
• Experience with version control and CI/CD tools such as GitHub and GitHub Actions
• Experience using Terraform for cloud infrastructure provisioning
• Familiarity with SDLC and modern data engineering best practices
• Strong organizational skills with the ability to manage multiple priorities and work independently

Nice to Have:

• Experience with data governance, lineage, or cataloging tools (Purview, Unity Catalog)

Responsibilities:

• Analyze, design, and develop enterprise data solutions using Azure, Databricks, Spark, Python, SQL
• Develop, optimize, and maintain Spark/PySpark data pipelines, addressing performance issues such as data skew, partitioning, caching, and shuffle optimization
• Build and support Delta Lake tables and data models for analytical and operational use cases
• Apply reusable design patterns, data standards, and architectural guidelines, including collaboration with 84.51° when needed
• Use Terraform to provision and manage cloud and Databricks resources (Infrastructure as Code)
• Implement and maintain CI/CD workflows using GitHub and GitHub Actions
• Manage Git-based workflows for Databricks notebooks, jobs, and data engineering artifacts
• Troubleshoot failures and improve reliability across Databricks jobs, clusters, and data pipelines
• Apply cloud computing skills to deploy fixes, upgrades, and enhancements in Azure environments
• Collaborate with engineering teams to enhance tools, systems, development processes, and data security
• Participate in the development and communication of data strategy, standards, and roadmaps
• Create architectural diagrams, interface specifications, and design documentation
• Promote reuse of data assets and contribute to enterprise data catalog practices
• Provide timely support and communication to stakeholders and end users
• Mentor team members on data engineering best practices and emerging technologies

This is an excellent opportunity for a highly technical, senior candidate to join Kroger’s data engineering team and work on cutting-edge Azure Databricks and Spark solutions.