As the Head of Data Engineering at Ambyint, you will lead the vision, strategy, and execution of our enterprise data architecture and roadmap. You will manage and empower a high-performing team of data engineers and data analysts, setting technical standards to support our market-leading artificial lift optimization platform. You’ll be instrumental in shaping our long-term data strategy - balancing scalability, security, cost efficiency, and platform performance.

Working closely with executive leadership, product managers, data science leaders, and software engineering heads, you will drive business outcomes by turning complex industrial data streams into scalable, reliable data products. Set the strategic vision and multi-year roadmap for enterprise data architecture, platform scaling, analytics, and streaming/batch capabilities. Lead, mentor, and recruit a world-class data engineering team, driving career development and team performance.

Partner with executive leadership, Data Science, and Product to align data engineering priorities with business goals. Drive the analytics and business intelligence strategy, delivering self-service reporting capabilities, executive dashboards, and enterprise data models. Establish enterprise DataOps standards, continuous integration/deployment (CI/CD) pipelines, and rigorous engineering practices.

Define and enforce data governance, quality frameworks, lineage, and metadata management across all data assets. Own SOC2 compliance, data privacy, and security protocols across all data stores and cloud infrastructure. Establish governance, semantic consistency, and quality controls across BI platforms and reporting models to guarantee single-source-of-truth analytics.

Manage the data platform budget, optimizing cloud warehouse consumption and other vendor tooling costs.



Oversee cross-functional delivery schedules, resource allocation, and technical debt management across pipelines and platform infrastructure. Evaluate and select emerging technologies, vendors, and tools to maintain competitive technical advantage.

Optimize BI platform licensing, analytics warehouse queries, and dashboard reporting infrastructure to maximize ROI on analytics spend. Data Strategy & Architecture Develop and maintain the quarterly roadmap for Data Engineering and deliver ≥ 85% of committed quarterly roadmap milestones on time. Have stakeholders in data science, product, and engineering rate the data product use ≥ 4/5 in a semi-annual satisfaction survey for meeting their data needs.

Keep annual regretted attrition under 10%, give every team member a documented development plan, and score at or above the company benchmark on team engagement surveys. Pass SOC2 audits with no data-related exceptions, with a governance framework (ownership, lineage, access controls) in place across all production datasets. Manage the data platform spend within budget while lowering unit cost per well year over year.

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related quantitative field. 8+ years of progressive experience in data engineering, with 3+ years in a leadership, managerial, or staff/principal architectural role. Proven track record of designing, deploying,



and scaling enterprise data platforms handling high-volume IoT, streaming, and batch data. Deep technical expertise in cloud data warehouses (Snowflake, Databricks, or BigQuery), ETL platforms (Azure data pipelines, Fivetran, Stitch), and modern orchestration/transformation tools (dbt, Airflow, Dagster).

Strong background in financial management for cloud resources, compute unit cost optimization, and FinOps best practices. Expertise in establishing DataOps processes, CI/CD frameworks, unit testing paradigms, and SOC2/data governance policies. Demonstrated ability to build, manage, and scale high-performing engineering teams through effective hiring, coaching, and retention.

Executive-level communication and stakeholder management skills with the ability to translate complex technical concepts into strategic business outcomes.

Experience managing end-to-end Business Intelligence (BI) platforms, data modeling for analytics, and working with modern visualization tools (e.g., Tableau, Power BI, Looker). comes from the satisfaction of your ‘customers’ You are curious, creative, biased for action, and The opportunity to make a difference in a cutting-edge technology company that is highly spirited and focused onbeing a leading contributor in the energy transition space. COMMITMENT TO DIVERSITY, EQUITY, & INCLUSION

At Ambyint, diversity, equity, and inclusion are at the core of who we are. Our commitment to these values is unwavering - across all of our work, teams, and interactions with customers. The understanding that having wide-ranging perspectives and backgrounds helps generate richer ideas to solve the complex problems of a changing, and increasingly diverse world is paramount to who we are and how we work together as a team. #

📌 Head of Data Engineering (Calgary)
🏢 Ambyint
📍 Calgary