Analytics Engineer II
Raleigh, North Carolina, United States
Jewelers Mutual
Protect your jewelry with the best jewelry insurance company, backed by a century of expertise and over 11,000 5-star reviews. Get a free quote in under 30 seconds.Summary
We are seeking an experienced Analytics Engineer to join our Data Management team. In this role, you will be responsible for designing, building, and maintaining data transformation pipelines that convert raw data into actionable, well-modeled datasets for business intelligence, reporting, and advanced analytics. Working closely with software engineers—who manage data ingestion and the underlying data platform—and other stakeholders, you will empower our organization with reliable, high-quality
data products. This role bridges the gap between raw data and meaningful insights, ensuring our data ecosystem supports strategic decision-making.
What You'll Do
- Design, develop, and maintain scalable transformation pipelines that shape raw data into structured, analytics-ready models using SQL, Python, and modern data orchestration tools.
- Collaborate with data analysts, data scientists, and business stakeholders to define and implement target data models that meet analytical and reporting needs.
- Capture data quality rules and implement testing frameworks (e.g., data validation, unit tests) to ensure the reliability, integrity, and correctness of transformed data.
- Create and maintain clear documentation of data models, transformation logic, and pipeline processes to support team collaboration and knowledge sharing.
- Stay current with industry trends and tools, advocating for best practices in data transformation, version control (e.g., Git), and analytics engineering workflows.
- Monitor pipeline performance and troubleshoot issues in collaboration with data platform engineers, ensuring seamless data flow from ingestion to analytics.
What We're Looking For
- 4-6 years of experience in analytics engineering, data engineering, or a related role, with a strong focus on data transformation and modeling.
- Proficiency in SQL for querying and transforming large datasets.
- Experience with data transformation tools like dbt (data build tool) or similar.
- Familiarity with Python or another scripting language for pipeline development.
- Knowledge of data orchestration platforms (e.g., Apache Airflow, Prefect).
- Experience with modern data platforms (e.g., Databricks, Snowflake, BigQuery).
- Proficiency in data warehousing techniques (star schema, data vault 2.0)
- Experience with version control systems (e.g., Git).
Leadership Responsibilities
- None
Certificates, Licenses, Registrations
- None
Physical Requirements
- Prolonged periods sitting at a desk and working on a computer.
- Occasionally required to stand; walk; use hands to finger, handle, or touch objects or controls.
What We Offer
- Great Place to Work® Certified: Join a team recognized for an environment of innovation and growth.
- Collaborative & Inclusive Culture: Work alongside smart, passionate peers who value ownership and continuous learning.
- Modern Work Environment: Enjoy a state-of-the-art office in Raleigh’s North Hills, combined with a hybrid work model that balances teamwork and flexibility.
- Competitive Compensation & Benefits: Comprehensive healthcare, 6% 401k matching, generous PTO (including floating holidays), and One Pass for fitness subscriptions.
- Community & Giving: Benefit from 50% charitable gift matching and paid volunteer time to support nonprofit causes.
At Jewelers Mutual, we’re empowering the jewelry industry with technology and building the future of our business. If you’re ready to take on a meaningful challenge and contribute to a growing team in a fast-paced environment, we’d love to hear from you.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow BigQuery Business Intelligence Databricks Data management Data quality Data Warehousing dbt Engineering Git Nonprofit Pipelines Python Snowflake SQL Testing
Perks/benefits: Career development Competitive pay
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