Senior Data Engineer
About The Position
Grainger's Product Discovery organization is investing in modern data engineering capabilities that support search platforms, search relevance, machine learning, analytics, and emerging AI-enabled experiences. The Senior Data Engineer designs and operates reliable, governed batch and real-time data products using technologies such as Databricks, Snowflake, Spark, Kubernetes, vector and search technologies, and cloud-native services. The role builds pipelines, data assets, orchestration patterns, and search and retrieval capabilities that make trusted data available to search, machine learning, analytics, and engineering teams. The position designs, develops, and maintains scalable data solutions that integrate and transform information for business and analytical use. It applies data engineering practices to deliver reliable, high-quality data products and improve data-process performance, scalability, and automation. The Senior Data Engineer partners with technical and business stakeholders to translate requirements into effective data solutions, and helps shape architecture, roadmaps, adoption, and operational ownership of data capabilities.
Requirements
- Bachelor's degree or equivalent experience in Computer Science, Computer Engineering, Information Systems, Data Science, Software Engineering, or a closely related technical field.
- At least 3 years of related data engineering or software engineering experience.
- Experience building and operating production batch and streaming data pipelines on Databricks or similar modern data platforms.
- Strong software engineering skills in Python and hands-on experience using Spark or other distributed processing frameworks.
- Hands-on experience with CDC, streaming/event-driven architectures, and workflow orchestration, with the ability to select patterns based on scale, reliability, and use case.
- Experience with containerization and orchestration technologies such as Docker and Kubernetes, along with cloud platforms such as AWS or equivalent.
- Experience implementing CI/CD and automated testing using platforms such as GitHub Actions or equivalent.
- Experience working across relational, NoSQL, vector, graph, or other database technologies and selecting storage patterns based on the use case.
- Experience designing and developing scalable data pipelines, data integration solutions, and data products.
- Proficiency with programming, scripting, and data query languages used to develop and manipulate data solutions.
- Experience translating requirements into technical designs and implementing solutions involving multiple data sources.
- Knowledge of modern data engineering.
Nice To Haves
- Experience with CDC and orchestration platforms such as AWS DMS, Debezium, Tableflow, Airflow, Databricks Workflows, or equivalent technologies.
- Experience using machine learning or AI within data pipelines to classify, enrich, standardize, match, or improve data.
- Experience with e-commerce, search, recommendations, or personalization platforms.
- Working knowledge of machine learning models and production of ML workflows.
Responsibilities
- Design, develop, test, and maintain scalable data pipelines and data products that integrate information from multiple sources.
- Build solutions to extract, transform, integrate, and deliver reliable data for analytical and business needs.
- Develop and enhance data engineering capabilities that improve data accessibility, performance, quality, and scalability.
- Analyze requirements and translate business and technical needs into data designs, specifications, and solutions.
- Identify and implement improvements to data engineering processes, including automation, optimization, and increased reliability.
- Partner with technical and business stakeholders to resolve data-related challenges and deliver solutions that meet business requirements.
- Provide technical guidance, review designs, and help establish engineering practices for less-experienced team members.
- Design and deliver scalable batch and streaming data pipelines and data products across modern data and cloud platforms.
- Define reusable data engineering patterns for CDC, event-driven processing, workflow orchestration, data products, and AI/search-enabled workloads.
- Partner with Engineering, Product, and Applied Science to shape architecture, roadmap, adoption, and operational ownership of data capabilities.
Benefits
- Medical, dental, vision, and life insurance coverage starting on the first day of employment.
- Six free sessions each year with a licensed therapist.
- 18 paid time off days annually for full-time employees, prorated based on employment start date.
- Six company holidays per year.
- 6% company contribution to a 401(k) Retirement Savings Plan each pay period, with no employee contribution required.
- Employee discounts.
- Tuition reimbursement.
- Student loan refinancing.
- Free access to financial counseling, education, and tools.
- Maternity support programs and nursing benefits.
- Up to 14 weeks of paid leave for birth parents and up to 4 weeks of paid leave for non-birth parents.
- Incentive target of up to 10%, based on individual and company performance objectives.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
