Data Engineer IV

Job not on LinkedIn

🔥 0 minutes ago

🌽 Illinois – Remote

🌽 Illinois – Remote

💵 $134.1k - $223.5k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 2%

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• Just posted.
• Jobs at this company usually fill in 32 days.

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Grainger

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1927

🏥 Healthcare

📦 Logistics

🏭 Manufacturing

Healthcare • Logistics • Manufacturing

Grainger is a leading broad line distributor that operates primarily in North America, Japan, and the United Kingdom. With a mission to "Keep the World Working", Grainger serves over 4. 5 million customers by offering around 2 million maintenance, repair, and operating (MRO) products and services, as well as access to millions of additional products through its online platforms. The company is recognized for its commitment to excellent service and innovative technology that enhances customer relationships and operational efficiency.

📋 Description

• Design and operate pipelines, data assets, semantic models, search and retrieval layers, and platform patterns that make trusted data available for analytics, AI agents, and operational decision-making • Design and implement highly efficient, reusable, and scalable data processing systems and pipelines across Kubernetes, Databricks, Snowflake, and related cloud services • Define platform patterns for AI-ready data products, including governed data assets, semantic models, vector and search capabilities, retrieval patterns, and integration points for Snowflake, Databricks, and other AI-enabled workflows • Evaluate, implement, and operationalize Snowflake AI initiatives including Cortex Analyst, Cortex Search, Cortex Agents, Cortex Code, Cortex Sense, and related AI/LLM-enabled data engineering features • Support Databricks requests from data engineering and analytics teams, including job orchestration, reusable pipeline patterns, performance tuning, production troubleshooting, workspace standards, and best-practice guidance • Use and evaluate AI-assisted engineering tools such as Claude, Claude CLI, GitHub Copilot, and related agentic tooling • Design with test-driven development and implement solutions for data reliability, accuracy, observability, and operational resilience • Develop data models and mappings, build new data assets, and perform exploratory data analysis on existing products and datasets • Educate data engineering teams on new data patterns, platform capabilities, AI-enablement approaches, and tools • Evaluate emerging technologies and multi-agent engineering environments for Grainger requirements • Work within an Agile delivery / Kanban methodology to deliver product increments iteratively • Work with product and business partners to define roadmaps, communication, architecture, adoption plans, and support models • Mentor junior team members and raise the technical bar for data engineering practices across the organization

🎯 Requirements

• 3+ years of experience in batch and streaming data engineering using Spark, Python, Scala, Snowflake, or Databricks for analytics, data engineering, or machine learning workloads • 3+ years orchestrating and implementing production pipelines with Databricks Workflows / Lakeflow Jobs, Apache Airflow, Luigi, or similar orchestration platforms • Hands-on Databricks platform experience in a central data platform or data engineering enablement role, including notebooks/repos, Delta Lake, Unity Catalog, Databricks Runtime, job/serverless/cluster compute, workflow monitoring, cost and performance optimization, and production support of user requests • Experience or strong working familiarity with Snowflake AI and Cortex capabilities such as Cortex Analyst, Cortex Search, Cortex Agents, Cortex Code / Snowflake CoCo, Cortex Sense, AISQL / AI functions, semantic models, and AI-enabled search, retrieval, or agent patterns • Comfort working with AI-assisted developer and agent tools such as Claude, Claude CLI, GitHub Copilot, or similar tools • Understanding of emerging multi-agent system patterns, including context management, tool use, orchestration, guardrails, testing, observability, and secure enterprise adoption • 5+ years of experience preparing structured and unstructured data for data science, analytics, machine learning, or AI-enabled applications • 4+ years of experience with containerization and orchestration technologies such as Docker and Kubernetes • Experience with shell scripting in Bash, Unix, or Windows shell preferred • Experience working with vector databases, graph databases, relational databases, and NoSQL stores • Experience using machine learning or AI in data pipelines to discover, classify, enrich, standardize, and clean data • Experience implementing CI/CD with automated testing in Jenkins, GitHub Actions, GitLab CI/CD, or similar tooling • Familiarity with AWS or other cloud services such as AWS Glue, Athena, Lambda, S3, and DynamoDB • Demonstrated experience implementing the data management lifecycle using data quality functions such as standardization, transformation, rationalization, linking, matching, monitoring, and stewardship • Position is not eligible for visa sponsorship

🏖️ Benefits

• Medical, dental, vision, and life insurance plans starting on day one • 6 free sessions each year with a licensed therapist • 18 paid time off (PTO) days annually for full-time employees • 6 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 • Nursing benefits • Up to 14 weeks paid leave for birth parents • Up to 4 weeks paid leave for non-birth parents • Incentive target of up to 15% based on individual and company performance objectives

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