Analytics Engineer

Our client is seeking an Analytics Engineer to support the modernization of the business intelligence and data modeling ecosystem. This role will play a key part in evolving the BI layer, including refactoring and rebuilding semantic models, and supporting migration efforts across data platforms.

The ideal candidate will have strong experience bridging data engineering and analytics, with a focus on building clean, scalable data models and enabling intuitive, reliable reporting. This role will partner closely with Analytics, BI, and Engineering teams to simplify complex logic, improve data accessibility, and drive consistency across reporting.

Responsibilities

• Design and develop scalable, well-structured data models to support business intelligence and analytics use cases.
• Refactor and simplify existing BI semantic layers (e.g., Looker explores / LookML) to improve usability, performance, and maintainability.
• Lead and support BI migration efforts, including rebuilding dashboards and underlying data models.
• Translate business requirements into clean, reliable datasets for self-service analytics.
• Partner with cross-functional stakeholders to define metrics, standardize logic, and ensure consistent reporting.
• Build and maintain ELT pipelines to transform and integrate data from multiple sources.
• Support data platform migration and replication efforts, ensuring data accuracy and integrity.
• Identify and resolve data quality issues and performance bottlenecks.
• Establish and promote best practices for data modeling, documentation, and governance.

• Bachelor's degree in a quantitative or technical field (e.g., Computer Science, Engineering, Mathematics, Statistics).
• 3+ years of experience in analytics engineering, data engineering, or a related role.
• Advanced proficiency in SQL and strong understanding of dimensional modeling and data warehousing concepts.
• Hands-on experience with BI tools, particularly Looker (LookML, explores, dashboards).
• Experience refactoring or rebuilding BI layers and semantic models.
• Experience supporting BI migrations (dashboard rebuilds, metric standardization, model redesign).
• Familiarity with modern data stack tools (e.g., dbt, Airflow).
• Experience with cloud data warehouses (Snowflake and/or Redshift).
• Ability to work with complex legacy systems and drive simplification.
• Strong communication and collaboration skills.
• Experience with data replication or integration is a plus.
• Familiarity with Python or other scripting languages is a plus.

Team Culture / Work Environment

• Collaborative
• Supportive
• Quick to respond
• Autonomy and ability to work independently

Top Candidate Skills & Application

1. Advanced SQL & Data Modeling Expertise: Designs and builds scalable datasets; refactors complex legacy queries and BI models into simplified, performant data models.
2. Analytics Engineering Mindset: Translates business requirements into reliable datasets and standardized metrics; ensures consistency across reporting.
3. Data Architecture & Pipeline Understanding: Understands end-to-end data flow; supports data migration, replication, and troubleshooting across systems.