Senior Data Engineer - $115,000 - $140,000 A Year
Senior Data Engineer at Aviva Canada driving the enterprise data modernization program: designing and building scalable data pipelines and architecture on Snowflake, dbt, AWS, SQL, Python and Terraform to power analytics and AI, while setting engineering standards, ensuring data governance, and mentoring other engineers.
- Compensation
- CA$115K–CA$140K / yr
- Location
- Winnipeg, Canada
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 8+ years professional experience delivering 10+ high-impact data projects end to end
- 2-5 years of Snowflake, dbt Core/Cloud, and AWS Cloud technologies
- 5+ years coding in multiple programming languages such as Python, Java
- Deep knowledge of relational databases (Snowflake, PostgreSQL, Amazon Aurora), big data platforms (Hadoop), and NoSQL databases (e.g. MongoDB)
- Skilled in tools such as Snowsight, Streamlit, Qlik, and SAP BusinessObjects
- Expert-level proficiency in SQL, Python, Shell, and Terraform with focus on performance, reusability, and maintainability
- Strong technical and business presentation skills; can identify and address gaps in data designs with stakeholders
- Hands-on experience with orchestration tools like Zena and AWS Managed Airflow
- Ability to thrive in fast-paced, ambiguous, high-pressure environments
- Strong interpersonal and communication skills; ability to lead teams and influence cross-functional stakeholders
Nice to have
- Familiarity with insurance industry processes and systems
- Experience operationalizing AI/ML and GenAI models
- Certifications: SnowPRO Core, SnowPRO Advanced Data Engineer (DEA-C01/C02), SnowPro Advanced Architect (ARA-C01), dbt Developer, AWS Cloud Practitioner
Full description
Aviva Canada is looking for a Senior Data Engineer to support our enterprise data modernization journey. You’ll use your expertise across modern and legacy platforms to build robust data pipelines and systems that power analytics and AI initiatives. In this role, you will contribute to the design and implementation of data solutions that support our growing business and next‑generation Snowflake platform.
What you’ll do
Technical Leadership: Define and drive the data engineering strategy, standards, and guidelines across the organization.
Solution Design: Develop high‑level and low‑level solution architectures, ensuring alignment with business and technical goals.
Data Pipeline Development: Lead the design and implementation of high‑performance data pipelines using tools like dbt Core/Cloud, ensuring scalability and maintainability.
Code Ownership: Write and maintain clean, reusable code in SQL, Python, Shell, and Terraform.
Quality & Governance: Champion data quality, governance, and cataloging practices;
create and reviewtest plans to validate data solutions.
Issue Resolution: Perform root cause analysis and implement effective solutions for complex data issues.
Agile Delivery: Lead agile ceremonies, foster a delivery‑focused mindset, and ensure timely execution of data initiatives.
Mentorship: Guide and mentor Data Engineers and project team members, elevating team capabilities and engineering excellence.
Collaboration: Work closely with architects, designers, QA engineers, and delivery teams to ensure cohesive and customer‑centric data products.
Documentation: Produce and maintain comprehensive technical documentation to support implementation and knowledge sharing.
Talent Development: Contribute to hiring by designing technical challenges, conducting interviews, and supporting onboarding.
What you’ll bring
8+ years of professional experience delivering over 10 high‑impact data projects from inception through warranty.
2–5 years of Snowflake, dbtCore/Cloud, and AWS Cloud Technologies.
5+ years of experience with coding in multiple programming languages such as Python, Java, etc.
Deep knowledge of relational databases (Snowflake, PostgreSQL, Amazon Aurora), big data platforms (Hadoop), and NoSQL databases (e.G., MongoDB).
Skilled in tools such as Snowsight, Streamlit, Qlik, and SAP BusinessObjects to communicate insights effectively.
Expert‑level proficiency in SQL, Python, Shell, and Terraform, with a strong focus on performance, reusability, and maintainability.
Strong technical and business presentation skills;