Senior Director, Reporting & Analytics Engineering

Overview

Lead the Enterprise Reporting and Analytics Engineering organization to turn engineered data into actionable decisions. You will guide a ~30-person team spanning analytics engineers, report developers, and data leaders, shaping a multi-year data strategy and governance.

The role blends governance with proactive, AI-enabled analytics to productize models and deliver timely insights. You’ll partner across Data Engineering, Data Science, Product Management, and Analytics Operations to create scalable, governed analytics products that drive business outcomes.

This is a transformative leadership role at the intersection of data, analytics, and enterprise decision-making.

Responsibilities

• Lead and develop an org of ~30 people, including frontline managers; manage hiring, career paths, performance, and succession.
• Define multi-year vision and quarterly outcomes for enterprise reporting and analytics engineering; align with cross-functional partners.
• Own budget, vendor relationships, and offshore capacity; sustain engineering culture with CI/CD, testing, and documentation.
• Advance last-mile architecture with semantic layers, curated data products, and certified datasets for reporting, AI enablement, and data science.
• Oversee enterprise metric layer for governed definitions across consumption points.
• Collaborate with Data Engineering to define contracts between pipeline/platform work and last-mile modeling; manage performance and cost.
• Drive data governance, metadata, lineage, and data quality efforts; ensure data security and access control.
• Lead enterprise visualization initiatives using platforms like Domo and Tableau; set standards for design, adoption, and cost management.
• Partner with Data Science to productize models, enable generative AI, and implement AI-enabled analytics with guardrails and accuracy monitoring.
• Establish intake and prioritization processes with Product Management and Analytics Operations; encourage reuse and transparent capacity planning.

Key requirements

• 15+ years in data/analytics or BI, with 8+ years leading teams and 4+ years managing managers.
• Experience leading a large, matrixed organization (25+ people).
• Strong SQL, dimensional modeling, ELT/ETL design; hands-on with cloud data warehouses (e.g., Snowflake, Databricks, BigQuery, Redshift, Synapse) and dbt.
• Software-engineering practices in analytics: Git workflows, automated testing, CI/CD.
• Experience with BI/visualization platforms (Domo, Tableau, Power BI, Looker) including governance and cost management.
• Proven data governance experience (catalog, lineage, glossary, stewardship) using platforms like Atlan/Collibra/Alation/Informatica.
• Collaborative track record with Data Engineering, Product Management, and Data Science; accountable ownership boundaries.
• Experience operationalizing Data Science outputs for business use; statistics knowledge for anomaly detection (seasonality, forecasting, control limits).
• Experience managing budgets, vendor contracts, and platform licensing.
• Executive communication
• Influence and stakeholder management
• Cross-functional collaboration
• SQL proficiency
• Dimensional modeling
• ELT/ETL design

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