Vice President, Data Engineering

Air-tek; Toronto; On-site; CAD 130,000 - 160,000; Full time

Job summary

A leading software company in Toronto seeks a Vice President of Data Engineering to lead the development of their data platform and manage a team focused on innovative solutions in the travel industry. The ideal candidate will have 7-10 years of experience and expertise in ETL processes and cloud environments such as AWS, GCP, or Azure. This role offers significant leadership responsibilities and collaboration opportunities with various teams.

Qualifications

• 7-10+ years in data engineering, with expertise in building data platforms.
• 4+ years leading teams and managing hiring/performance.
• Proven track record delivering scalable solutions in cloud environments.

Responsibilities

• Lead the charge in designing and building our data platform.
• Build and maintain the systems that handle data including pipelines.
• Architect and build a scalable data platform using cloud infrastructure.
• Manage your team, delegating tasks and conducting performance reviews.
• Collaborate with product managers on data needs for new products.

Skills

Deep knowledge of data architecture, ETL/ELT processes

Proficiency in Python, SQL, Scala

Strong communication skills

Leadership skills to delegate and mentor

Education

Bachelor’s or Master’s in Computer Science, Engineering

Tools

AWS

GCP

Azure

Apache Kafka

Airflow

Snowflake

Databricks

Spark

Job description

Air-tek is a Canadian-based software company with a powerful suite of unique products that has already achieved a significant share of a huge global opportunity. The product market fit is excellent, and customers are lining up to buy. Although our global customers know us, we intentionally operate in stealth mode during this growth phase.

Our diverse team shares a collective passion for solving complex problems with a drive to innovate and a desire to create the passenger-centric travel industry. Based in Toronto, our inclusive culture is built on trust, collaboration, delivering a great product, and continuous personal development. We love what we do, and we support the team around us.

As our Vice President, Data Engineering, you’ll be the cornerstone of our data team, reporting directly to our Founder/CEO. You’ll lead the charge in designing and building our data platform, pipelines, and integrations, support data products and machine learning initiatives, and build/manage the team that will execute these goals. You’ll lead the charge in hiring and growing the team, ensuring scalable, reliable data solutions that align with our integration-heavy projects. Collaborating closely with engineering, customer delivery and product management, you’ll drive data excellence in a fast-paced, high growth environment.

Key Responsibilities

• Technical Leadership:
• Build and maintain the systems that handle data including pipelines, databases, data warehouses and ensuring data quality and accessibility.
• Design and implement data storage solutions, creating ETL processes, managing data infrastructure, and ensuring data is available and reliable for analysis.
• Architect and build a scalable data platform (e.g., data lakes, warehouses) using cloud infrastructure to support enterprise integrations and data products.
• Develop robust data pipelines for real-time and batch processing, enabling customizations and new product initiatives.
• Design and implement data integrations with platforms like MuleSoft, ensuring seamless data flows for cross-team projects.
• Support machine learning initiatives by building pipelines for model training, feature engineering, and data preprocessing, collaborating with future data scientists.
• Create data products (e.g., dashboards, APIs) to empower internal teams and customers, aligning with product manager requirements.

• Team Management:
• Build the team from scratch, defining roles and selecting candidates with complementary skills (e.g., pipeline development, ML ops).
• Manage your team (data engineers, data analysts), delegating tasks, mentoring, and conducting performance reviews.
• Foster team autonomy by empowering reports to own tasks (e.g., pipeline maintenance, dashboard creation) while ensuring alignment with project goals.

• Collaboration and Coordination:
• Work within pods alongside customer delivery, developers, DevOps, and solution architects; logging milestones and dependencies.
• Partner with engineering/product and leadership to standardize data requirements for integrations, reducing delays, and rework.
• Collaborate with product managers on data needs for new products, ensuring integration of compatibility.
• Provide technical input during strategic meetings to ensure alignment and technical scalability.

• Resource and Risk Management:
• Use resource tools to optimize team capacity and infrastructure allocation, avoiding bottlenecks (e.g., compute shortages for pipelines).
• Identify and mitigate risks (e.g., data quality issues, integration delays), escalating data governance, security, compliance and performance risks or issues to key internal colleagues.

• Skills:
• Deep knowledge of data architecture, ETL/ELT processes, and real-time/batch processing.
• Proficiency in programming (e.g., Python, SQL, Scala) and infrastructure-as-code (e.g., Terraform).
• Strong communication to collaborate with Delivery Leads, product managers, and pods.
• Leadership skills to delegate, mentor, and foster team autonomy while driving results.

Experience & Education

• 7-10+ years in data engineering, with expertise in building data platforms, pipelines, and integrations.
• 4+ years leading small teams (2-5 people), mentoring engineers, and managing hiring/performance.
• Proven track record delivering scalable data solutions in cloud environments (AWS, GCP, Azure).
• Experience with integration platforms (e.g., Apache Kafka) and data tools (e.g., Airflow, Snowflake, Databricks, Spark).
• Familiarity with machine learning pipelines (e.g., feature stores, model training data) is a plus.
• Bachelor’s or Master’s in Computer Science, Engineering, or related field (or equivalent experience).