Data Engineering Manager, Business Intelligence

Summary

Join Movable Ink as a Data Engineering Manager, Business Intelligence to lead a high-impact team in designing and implementing star schema data models. You will own the data architecture, champion data governance and quality, and drive the adoption of OpenMetadata. Mentor and develop engineers while transforming complex business data into scalable data products. This role blends technical leadership with stakeholder collaboration, shaping data leverage for strategic decision-making. The position is primarily remote with occasional visits to the Toronto office. You will manage a team, build ETL/ELT pipelines, and optimize data models for quick query response times. You will also implement data quality checks and reporting to ensure data trustworthiness.

Requirements

• 6+ years of data engineering experience, including 2+ years in dimensional modeling and star schema design
• 2+ years managing and mentoring data engineering teams, balancing leadership with hands-on contributions
• Expert-level SQL skills, with deep experience in Amazon Redshift, Snowflake, or similar columnar databases
• Strong experience with Apache Airflow for data pipeline orchestration, including scheduling, dependency management, and DAG optimization
• Hands-on experience with ETL/ELT development, transforming raw data into structured, analysis-ready datasets using Python, dbt or other transformation frameworks
• Proven ability to design high-performance data models, including slowly changing dimensions (SCD), fact tables, and surrogate keys for historical point-in-time analytics
• Experience implementing and managing a Data Catalog (OpenMetadata preferred) for governance and discoverability
• Hands-on expertise in data quality testing, monitoring, and anomaly detection frameworks
• Proficiency in Tableau (or similar BI tools) to optimize reporting performance and self-service analytics
• Strong ability to translate business needs into scalable, reliable data solutions for internal stakeholders and product insights
• Excellent communication and stakeholder collaboration skills, ensuring alignment across engineering, analytics, and business teams

Responsibilities

• Design and implement star schema data models across business domains and product analytics, ensuring dimensional modeling best practices
• Manage a team of data engineers, including hiring, mentoring, and professional development in a collaborative, high-performing culture
• Build ETL/ELT pipelines using Airflow that reliably populate fact and dimension tables in our Redshift environment
• Partner with product teams and business stakeholders to translate reporting requirements into effective data models that serve both internal analytics and customer-facing features
• Optimize data model performance for quick query response times in Tableau dashboards and product reporting interfaces
• Reduce time to insights by optimizing data pipelines, transformation logic, and data delivery processes, ensuring stakeholders and product teams have fast, reliable access to actionable data
• Develop data transformations that enable accurate historical reporting while supporting intra-day data updates for real-time insights. Implement robust data lineage tracking to ensure transparency, traceability, and trust in data workflows, enabling stakeholders to understand the origin, transformations, and dependencies of key business metrics
• Implement automated data quality checks, anomaly detection, and reporting to ensure stakeholders and customers trust and rely on our datasets

Preferred Qualifications

OpenMetadata

Benefits

This role is primarily remote, but we are looking for someone open to coming into our Toronto office once a month