Senior Data Engineer

TEEMA; North Vancouver; On-site; CAD 88,000 - 118,000; Full time

Job summary

TEEMA in North Vancouver, BC, is seeking a Senior Data Engineer to design scalable data architectures and enterprise data products using Azure, Databricks, Delta Lake, Spark/PySpark, SQL, and Python. You will build reusable datasets and lead end-to-end data pipelines across multiple business domains.

You will drive data quality, observability, governance, and metadata standards while partnering with Product Managers and cross-functional teams to deliver high-impact data capabilities and scalable

Qualifications

• 5-8+ years of Data Engineering experience across enterprise data platforms.
• Proven ability to build cloud-native data platforms on Azure.
• Hands-on Databricks Lakehouse, Spark/PySpark experience.
• Advanced SQL and Python for ETL/ELT pipelines.
• Experience with Delta Lake and data governance concepts.
• Knowledge of metadata, lineage, and data quality practices.
• Familiarity with CI/CD and DevOps in data environments.
• Ability to design scalable, enterprise-grade data architectures.

Responsibilities

• Design and implement scalable data architectures and enterprise data products.
• Build enterprise-level common entities and reusable datasets across domains.
• Develop, maintain, and optimize scalable ETL/ELT pipelines.
• Lead data quality, observability, reliability, and trust initiatives.
• Support automated data validation, monitoring, and alerting frameworks.
• Establish metadata, lineage, governance, and discoverability standards.
• Build governed data foundations for self-service analytics adoption.
• Collaborate with Product Managers and stakeholders to deliver data capabilities.
• Translate business requirements into scalable technical designs.
• Partner with Platform, Architecture, Security, and Governance teams for scalable solutions.
• Lead design reviews and contribute to architecture roadmaps.
• Define and promote CI/CD, testing, source control, and deployment practices.
• Mentor junior engineers through code reviews and design sessions.
• Identify opportunities to improve automation, productivity, and cost.
• Explore emerging technologies to enhance data delivery and analytics.

Skills

5-8+ years of Data Engineering

Cloud-native data platforms

Azure Data Platform

Databricks / Lakehouse

Spark / PySpark

SQL

Python

Tools

Databricks

Spark

Delta Lake

CI/CD tooling

Data governance tools

Job description

Job Title: Senior Data Engineer

Job ID: 89891

Location: North Vancouver, British Columbia

What you will be doing:

• Design and implement scalable data architectures and enterprise data products using Azure, Databricks, Delta Lake, Spark/PySpark, SQL, and Python

• Build enterprise-level common entities and reusable datasets serving multiple business domains

• Develop, maintain, and optimize scalable ETL/ELT pipelines and frameworks supporting operational and analytical workloads

• Lead initiatives focused on improving data quality, observability, reliability, and trust across enterprise datasets

• Support implementation of the DCE Data Quality Framework, including automated validation, monitoring, and alerting

• Establish and improve metadata, lineage, governance, and discoverability standards

• Build governed data foundations that enable greater adoption of self-service analytics

• Partner directly with Product Managers and business stakeholders to understand requirements, prioritize initiatives, and deliver high-value data capabilities

• Translate complex business requirements into scalable technical designs and solutions

• Partner with Platform, Architecture, Security, and Governance teams to ensure solutions are scalable, secure, and aligned with enterprise standards

• Lead technical and cross-functional design reviews and contribute to architecture and roadmap planning

• Define and promote CI/CD, testing, source control, infrastructure automation, and deployment best practices

• Mentor junior and intermediate engineers through code reviews, technical design sessions, and hands‑on coaching

• Identify opportunities to improve automation, engineering productivity, platform performance, scalability, reliability, and cost optimization

• Explore emerging technologies and approaches that improve enterprise data delivery and analytics enablement

What you must have:

• 5-8+ years of Data Engineering experience

• Strong experience building cloud-native enterprise data platforms

• StrongMicrosoft Azure Data Platformexperience

• Advanced hands-on experience with Databricks / Databricks Lakehouse

• StrongSpark / PySparkexperience

• AdvancedSQL and Python

• Strong ETL/ELT development and optimization experience

• Experience with Delta Lake

• Enterprise data modeling and dimensional design

• Experience building reusable enterprise data products and data assets

• Data quality monitoring and implementation

• CI/CD and DevOps practices

• Source control, automated testing, and deployment methodologies

• Strong understanding of scalable enterprise data architecture

Data Quality & Governance Experience

Candidates should have hands-on experience implementing or supporting:

• Data quality frameworks
• Automated data validation and monitoring
• Data observability
• Metadata management
• Data lineage
• Data governance
• Data contracts
• Governed/self-service data access

Salary/Rate: $75.00 per hour