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Added 12 mins ago
C&
Heavy Duty Cleaner - Part Time - 2nd shift
Cushman & Wakefield
Toronto, ON
- $18.11 to $21.3 CAD / hour
- Part-time
Added 12 mins ago
C&
Finance Manager - Business Unit Finance
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- Full-time
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PB
Head of Growth
Powered by search
Remote, Canada
- Full-time
- Remote
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Hamilton, ON
- $19 CAD / hour
- Part-time
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- Full-time
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Auto Body Parts Coordinator (Kitchener-Waterloo)
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Added 12 mins ago
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Manager, Global Technology & Operations (GTO) Strategy & Transformation
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Director, Talent Development (GRO) and Human Performance Enablement
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Ambyint

Head of Data Engineering

Calgary, AB, Canada

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Job details

Experience: 8+ years of progressive experience in data engineering, with 3+ years in a leadership, managerial, or staff/principal architectural role.
Posting language: English
Posted: Oct 29, 2026

Original job description

About the role
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.

WHAT YOU'LL DO

Strategy & Architecture Leadership
- 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.
Ops Excellence & Platform Governance
- 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.
Financial & Resource Management
- 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.
Leadership & Team Development
- Hit the approved hiring plan on schedule, with new hires fully productive within 90 days.
- 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.
Governance, Security & Cost
- 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.

QUALIFICATIONS

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).

WHAT SETS YOU APART

● The gratification of a job well done comes from the satisfaction of your ‘customers’

● It’s in your nature to be efficient and do it really well, while you always deliver on what you promise

● Your strengths come from collaborating with others

● Continuous learning and improvement are part of your mantra

● You are curious, creative, biased for action, and love solving problems

● You don’t assume that you are the best and have the humility to learn from others

WHAT SETS US APART

Ambyint is a scale-up company, possessing all the exciting edginess of a start-up with solutions that are proven and advancing daily. We pride ourselves on the strength of our team and company, and the positive environmental impact we are driving. We live by a simple and effective set of values.

WHAT’S IN IT FOR YOU

The opportunity to make a difference in a cutting-edge technology company that is highly spirited and focused on being a leading contributor in the energy transition space. We offer an environment steeped in creating a rewarding professional experience and having some fun along the way. We work in a hybrid working environment with a diverse and talented team. We have a passion for taking on big challenges to create a wealth of opportunities and we will support your development and career goals. Additionally, we offer a competitive compensation and benefits package.

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. They are central to our mission and to our impact. The understanding that having varied 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.

If you are a passionate professional that likes to work in a diverse team environment supporting an entrepreneurial culture with a focus on delivering exceptional value for our customers, we invite you to apply. This is your opportunity to join a growing company offering a competitive base salary and benefits.

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More about this job

Responsibilities

You will lead the vision, strategy, and execution of the enterprise data architecture while managing a high-performing team of data engineers and analysts. You will also drive business outcomes by establishing data governance, optimizing platform performance, and aligning data engineering priorities with executive leadership goals.

Requirements

The role requires a Bachelor’s or Master’s degree in a quantitative field and over 8 years of progressive experience in data engineering, including leadership roles. Candidates must demonstrate deep technical expertise in cloud data platforms, DataOps, and the ability to scale enterprise data infrastructure.

Skills

Data engineering
Data architecture
Team leadership
Cloud data warehouses
Snowflake
Databricks
BigQuery
ETL
dbt
Airflow
Dagster
DataOps
CI/CD
Data governance
Business intelligence
Stakeholder management

Benefits

Competitive compensation
Benefits package

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
Data Architecture
IoT
Streaming Data
Batch Data
Snowflake
Databricks
BigQuery
Azure Data Pipelines
Fivetran
Stitch
dbt
Airflow
Dagster
FinOps
DataOps
CI/CD
SOC2
Data Governance
Business Intelligence
Tableau
Power BI
Looker
Energy Transition
Artificial Lift Optimization
Cloud Infrastructure
Metadata Management
Data Modeling
Leadership
Strategy

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