Senior Analytics Engineer

Since the year 2000, OEC has grown globally to more than 1,000 employees with a double-digit revenue increase nearly every year. We provide a lively culture, employee rewards and recognition, and the opportunity to develop and implement innovative technology solutions.

Job Summary

As a Senior Analytics Engineer at OEC, you will be the backbone of our data layer - designing, building, and maintaining the models that power business decisions across the company. You will own critical areas of our dbt project, ensure Snowflake data assets are clean and trusted, and bring a modern, AI-assisted mindset to how we build and ship analytics.

This is a senior individual contributor role. You will lead by example, set standards, mentor peers, and collaborate closely with Data Scientists, Product Managers, and Engineers to turn raw data into reliable, documented, and governed analytical assets.

Key Responsibilities & Duties

• Design, build, and maintain scalable dbt models following modular, layered architecture.

• Own model performance: optimize Snowflake queries, configure materializations (incremental, table, view) and clustering strategies.

• Evolve dbt best practices: testing coverage, documentation, and source freshness checks.

• Code reviews for dbt PRs, establish modeling conventions, and contribute to the team’s analytics engineering playbook.

• Design Snowflake database and schema structures, manage roles and access controls, and optimize warehouse sizing.

• Monitor and reduce compute costs through query profiling, result caching, and warehouse auto-suspend policies.

• Partner with Data Platform/Engineering on ingestion pipelines, Snowpipe configurations, and external stage setups.

• Use Claude and other AI tools as a force multiplier: accelerate model generation, documentation writing, SQL refactoring, and test creation.

• Champion AI-assisted workflows within the team, sharing effective prompting patterns and use cases that improve team velocity.

• Explore agentic analytics workflows and contribute to their adoption.

• Partner with engineers and business stakeholders to translate analytical requirements into robust data models.

• Guide and mentor Associate and mid-level Analytics Engineers through code reviews, pairing sessions, and knowledge sharing.

• Define team conventions around naming, folder structure, model contracts, and testing thresholds.

Skills & Qualifications

• 5+ years of experience in analytics engineering, data engineering, or a closely related data role.

• Expert-level dbt (Core or Cloud): layered modeling, advanced testing, macros, packages (dbt-utils, dbt-expectations), and CI/CD integration.

• Deep Snowflake expertise: query optimization, materialization strategies, clustering and access control.

• Advanced SQL and performance tuning.

• Strong understanding of data modeling concepts.

• Experience building or maintaining BI semantic layers and working with tools such as Sigma, Looker, Tableau, or Power BI.

• Excellent documentation habits: you believe models without docs are technical debt.

• Strong written and verbal English communication - you can explain data decisions to both engineers and business stakeholders.

Strong Plus

• Hands-on experience with AI tools for development tasks: query writing, documentation, debugging, and code review.

• Python proficiency for data transformation tasks, pipeline scripting, or working with the dbt Python model interface.

• Experience with orchestration tools (Airflow, Dagster, or dbt Cloud jobs).

• Understanding of automotive parts, catalog, or marketplace data domains.

• Experience working in a product-led data team with exposure to event/product analytics.

Why You Should Join Us

Our vision is to make it fast and easy for auto repair shops to find the right parts across all of their suppliers with one search. Together, OEC’s team helped countless businesses save valuable time so they can focus on their customers — and we’re just getting started.

The position is fully remote, with the requirement to attend quarterly in-person meetings.

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