Senior Analytics Engineer - Business Intelligence

Job description

Job responsibilities

• Design, build, and own the data models that serve as the single source of truth for BI reporting — structuring tables, views, and semantic layers so metrics are defined once and used consistently across all dashboards…
• Design, build, and maintain ETL/ELT pipelines that feed those models, ensuring data is accurate, timely, and reliable at scale.
• Partner with data producers and business stakeholders to translate reporting and decision-making needs into durable data models and pipelines, rather than one-off dashboard logic.
• Define, instrument, and maintain business KPIs from scratch using SQL and Python, and ensure definitions stay consistent across teams and dashboards.
• Build and enforce data quality checks, validation processes, and documentation so stakeholders can trust the numbers behind leadership- and board-level reporting.
• Create and maintain actionable, user-friendly dashboards and visualizations (Tableau, Power BI, or similar) to provide valuable insight.
• Support and help evolve leadership-critical reporting deliverables, ensuring governed, well-documented data models rather than ad hoc queries.
• Help evolve the team’s data platform and architecture (e.g., improving legacy pipelines), balancing pragmatism with long-term maintainability.

Job requirements

• Bachelor’s degree in Computer Science, Data Engineering, Data Analysis, or a related field with 6+ years of experience OR a Master's degree with 3+ years of experience.
• Deep hands-on experience with data modeling and database/warehouse design — building governed, reusable data models that serve multiple downstream dashboards and reporting tools consistently.
• Strong SQL skills and proficiency in Python (pandas, PySpark, or similar) for pipeline development, transformation, and analysis.
• Hands-on experience building and maintaining source-of-truth ETL/ELT pipelines, including data quality checks and validation processes, in production environments.
• Experience with one or more BI tools (Tableau, Power BI, Looker, QuickSight, or similar), including enough hands-on dashboard-building experience to speak the language of BI analysts and evaluate their work.
• A track record of mentoring or leading other engineers or analysts — through reviews, pairing, documentation, or setting team standards.
• Comfort working with ambiguous, evolving requirements, and the ability to partner directly with stakeholders across the business to turn loosely defined problems into well-structured data models.
• Strong communication skills and the ability to document and explain technical decisions to both technical and non-technical audiences.