Lead Data Engineer
Location: Hybrid, Calgary
Salary: $140,000 - $180,000 CAD
About the Company
Our client is a well-established energy analytics company that has achieved product-market fit and is now in a growth phase.
They are a data-first organization. Data is not a support function here; it is the product. The data engineering team builds revenue-generating data products that customers rely on to make real-world decisions. This is an environment where strong engineers have a direct impact on the business.
About the Role
This role is remote to start, with plans to open an office in Calgary in the near future. For that reason, we’re only considering candidates who already live in Calgary or are open to relocating.
Data is at the core of the company’s platform, and they are hiring a Lead Data Engineer to help anchor and scale a new data engineering team in Canada.
This is a hands-on leadership role. You’ll own key architecture and system design decisions, build and operate high-performance data systems, and help modernize and expand the platform as the company continues its shift toward a more data-centric architecture. You’ll also play a critical role in mentoring engineers, setting technical standards, and driving complex projects forward in a high autonomy environment.
Responsibilities:
• Design, build, and optimize scalable, incremental data pipelines and lakehouse-based data systems.
• Own architecture and system design decisions, with a focus on performance, scalability, reliability, and long-term maintainability.
• Own solutions end-to-end, from design through deployment and ongoing operation.
• Drive technical planning, project execution, and clear communication across teams.
• Develop and orchestrate data workflows using tools like Airflow and modern ELT, ETL patterns.
• Build and maintain distributed data processing applications (Iceberg, Athena, Spark, or similar).
• Implement data governance, data quality, security, and compliance best practices.
• Design efficient storage and retrieval patterns across cloud environments and modern warehouses (S3, Iceberg, Snowflake, Redshift, BigQuery).
• Partner closely with engineering, product, data science, and customer-facing teams to translate data needs into reliable, scalable production systems.
• Monitor, troubleshoot, and continuously improve pipeline and platform performance.
• Provide hands-on mentorship, coach other engineers, and help raise the technical bar across the team.
• Support hiring by interviewing and helping evaluate future data engineering team members.
You Might Be a Great Fit If You…
• Have 10+ years of experience in data engineering, software engineering, or a closely related field
• Have strong Python and SQL skills
• Have hands-on experience with modern lakehouse architectures and tools such as Apache Iceberg, dbt, DLT, and similar technologies.
• Have designed and built modern data platforms, not just maintained them.
• Are comfortable working with batch, streaming, and incremental data processing patterns
• Have strong experience with orchestration tools like Airflow and distributed processing systems such as Spark.
• Apply strong software engineering fundamentals, including versioning, testing, CI/CD, and maintainable system design.
• Communicate clearly and can explain complex systems in a way that actually lands with different audiences.
• Are comfortable with ambiguity, take ownership, and move work forward without needing a rigid playbook.
• Have prior tech lead or leadership experience and enjoy mentoring others and improving how the team works.
• Have experience in small to mid-sized companies or thrive in environments with high ownership and few layers.
Preferred
• Hands-on experience with IaC tools such as Terraform, Pulumi, or CloudFormation.
• Experience with Docker, Kubernetes, and cloud platforms like AWS or GCP.
• Background working with open source-oriented stacks rather than highly prescriptive platforms.
Cultural Fit
You’ll be successful here if you:
• Bring a low ego, team-first mindset.
• Enjoy healthy technical debate and can disagree without turning it into a personality trait.
• Like working on small, highly collaborative teams.
• Are self-motivated, curious, and always looking to improve.
• Can influence without authority through clear thinking and communication.
• Are comfortable working cross-functionally to deliver real customer impact.
• Take ownership, follow through, and care about quality.
• Are flexible and willing to jump in where needed to help the team succeed.
• Like knowing what’s happening across the company and being part of it.
If you’re excited to lead, build, and scale real data products with a high-impact team, we’d love to talk.
