Senior Data Engineer, Analytics

Senior Data Engineer, Analytics at Lovevery, an individual contributor role centered on analytics engineering, data platform leadership, and enabling data-driven decision making.

Responsibilities

• Produce scalable data solutions that power faster development and confident business decisions, including pipelines, visualizations, dashboards, and related analytics artifacts; apply DBT to transform the data layer with confidence.
• Serve as a senior technical authority in data and analytics engineering, guiding architecture discussions and implementing robust, scalable data models.
• Balance feature delivery with simple, high-performance design; strive for cost-efficient pipelines that maintain strong performance.
• Collaborate to build and maintain a modern data warehouse architecture that unlocks insights through strategic design.
• Partner with Product Managers, Engineers, and Business Stakeholders to capture requirements and translate them into technical solutions.
• Work with power users to enable data fluency and empower self-serve reporting tools that unlock business value.
• Promote AI and automation in coding, documentation, and data exploration to streamline development and boost self-service capabilities.

Requirements

• 5+ years of experience implementing and scaling DBT in a team setting and growth environment.
• 5+ years of production data modeling using cloud-based warehousing technologies such as Databricks Delta, Snowflake, Redshift, or BigQuery, creating intuitive models that support self-service exploration and operational reporting.
• Very strong understanding of advanced SQL concepts and their performance implications.
• Familiarity with Spark or similar distributed data processing technologies.
• Proven track record building data pipelines on CI/CD platforms (e.g., GitHub Actions, CircleCI) with well-tested pipelines, proactive alerting, and solid data quality standards.
• Experience integrating AI and automation tools (e.g., GitHub Copilot, Natural Language Query tools) to accelerate development.
• Skilled in data visualization platforms such as Looker, Tableau, Power BI, or similar; strong preference for Omni; experienced in building dashboards and enabling self-serve capabilities for business users.
• Self service capabilities in Git.
• Python experience is a bonus.
• Experience with Prefect, Dagster, Airflow or other DAG tools is a bonus.
• Experience with subscriptions and/or ecommerce is a bonus.

Technologies

• DBT
• Databricks Delta
• Snowflake
• Redshift
• BigQuery
• Spark
• GitHub Actions
• CircleCI
• GitHub Copilot
• Natural Language Query tools
• Looker
• Tableau
• Power BI
• Omni
• Python
• Prefect
• Dagster
• Airflow
• Git

Benefits

• Competitive salary, benefits and stock option package
• 3 weeks PTO in year 1 plus 14 paid holidays
• Generous parental leave
• Equipment provided as needed to do the job
• Free or discounted Lovevery products
• Remote work option available anywhere in the US

About Lovevery

Lovevery is a fast growing digitally native brand headquartered in Boise, Idaho. Co founded by successful serial entrepreneurs, the company serves parents with science based early development experiences for children. Lovevery has earned recognition as one of Fast Company's 2024 Most Innovative Companies, and has garnered awards from TIME, Red Dot, Good Housekeeping and Forbes.

About the Role

This Senior Data Engineer, Analytics role shapes Lovevery's data strategy and drives data excellence across the business. It is a high impact individual contributor position with shared ownership of analytics engineering and opportunities to broaden ownership across the data stack. The role suits someone who consistently delivers high quality code for complex problems and embraces AI driven solutions to improve velocity and outcomes. You will join a team focused on strengthening transformation and visualization layers, and from day one lead initiatives on the data platform to empower decision makers.

About You

• Strategic Individual Contributor: Hands on developer with a vision, preferring ownership over oversight and energized by building, optimizing, and scaling analytics capabilities.
• Domain Fluent: Deep understanding of business metrics, their evolution, and how to equip others with data that drives action.
• Trusted Communicator: Bridges technical and non technical stakeholders, translating complex requirements into elegant data products.
• Results-Driven: Delivers clean, actionable data models and tools that enable informed decisions; minimizes dead code, unused dashboards, and messy schemas.
• AI-Forward Thinker: Seeks ways to apply generative AI and machine learning to data transformation, documentation, and user facing tooling to improve outcomes.