Senior Manager, Data Engineering – Analytics

This is a fully remote position, open to applicants in Canada.

📋 Description

• Lead, mentor, and develop a team of data and analytics engineers, which encompasses hiring, performance management, career development, planning, and establishing technical standards.

• Create a data engineering and analytics roadmap that is in alignment with the company’s objectives, prioritizing investments in data platforms, reporting requirements, analytics capabilities, and cross-functional data initiatives.

• Supervise the design, reliability, scalability, and governance of the organization's data infrastructure, including data warehouses, data lakes, ETL/ELT pipelines, orchestration systems, semantic layers, and BI tools.

• Ensure that business stakeholders have access to accurate dashboards, metrics, reports, and ad hoc analyses to facilitate decision-making across various functions such as product, operations, finance, sales, marketing, and executive leadership.

• Promote self-service as a company-wide objective by creating rich, trusted datasets and providing access through AI-driven natural language interfaces.

• Set standards for data accuracy, lineage, documentation, access controls, privacy, security, and compliance.

⛳️ Requirements

• Over 6 years of professional experience in data engineering and analytics, including more than 2 years in leadership roles overseeing teams of Senior Data/Analytics Engineers.

• Demonstrated expertise in managing data engineering, analytics engineering, BI, or analytics teams, encompassing hiring, coaching, performance management, and roadmap planning.

• In-depth knowledge of data warehouses, data lakes, ETL/ELT pipelines, orchestration, data modeling, BI platforms, semantic layers, and data quality practices.

• Practical experience with tools such as Snowflake, BigQuery, Redshift, Databricks, dbt, Airflow, Fivetran, Looker, Tableau, Power BI, or similar platforms.

• Proven ability to collaborate with executives and teams across product, operations, finance, engineering, sales, and marketing, translating business objectives into data strategies, dashboards, and analytics products that enhance decision-making.

• Established capability in building trusted, governed data products and facilitating organization-wide access through natural language or AI-driven analytics interfaces, with strong controls for accuracy, security, privacy, compliance, and usability.

• Experience in defining standards for data quality, documentation, access controls, privacy, security, auditability, metric definitions, and trusted data products, including compliance with SOX, SOC2, and international data policies and regulations (e.g., GDPR, data residency requirements).

• Bachelor’s degree in computer science, data science, engineering, statistics, mathematics, information systems, or a related field; advanced degrees are advantageous.

🏝️ Benefits

• Offers Equity