Senior Data Engineer in Vancouver

This role is intended for a Senior Data Engineer who combines deep technical fluency with proven delivery leadership, driving predictable execution, engineering discipline, and continuous improvement.

Key Responsibilities:

• Own solutioning and engineering practice across multiple tracks: scope, roadmap, milestones, dependencies, RAID, and change control.
• Establish and run governance cadence: weekly status, executive readouts, risk reviews, planning alignment, and steering updates.
• Drive delivery predictability and operational rigor through clear plans, measurable outcomes, and disciplined execution.
• Act as the primary delivery interface for customer stakeholders (Directors, Tech Managers, PgMs/PjMs, Product team, BSAs, Engineers, Architects).
• Translate business priorities into actionable plans with clear acceptance criteria, sequencing, and release milestones.
• Communicate proactively on progress, tradeoffs, risks, mitigations, and decisions required; manage escalations and align on next steps.
• Lead delivery across ingestion, streaming, transformation, orchestration, and data product enablement using: Airflow for orchestration, scheduling, dependency management, and operational SLAs; Kafka for event/stream processing patterns and reliability considerations; Databricks/Spark for processing and pipelines; Snowflake for warehousing/analytics, performance, and cost considerations; Postgres for operational data sources/integrations.
• Influence solution quality through technical governance: design reviews, coding standards, data modeling standards, performance practices, and reusable patterns.
• Ensure production readiness: monitoring/alerting, runbooks, incident response, root-cause analysis, and preventative actions across tracks.

Required Qualifications:

• 10+ years in technology, with 5+ years in data engineering leadership for complex programs (services/consulting experience strongly preferred).
• Proven success delivering multi-track programs with complex dependencies and senior stakeholder engagement.
• Deep experience in data engineering delivery including ETL/ELT, orchestration, data modeling, data quality, observability/monitoring, and production support.
• Technical fluency required to lead engineering outcomes and challenge decisions, including: SQL (advanced) and Python fundamentals; Snowflake and Databricks/Spark delivery experience; Airflow concepts; Kafka concepts; Postgres fundamentals.
• Strong Agile delivery experience (Scrum/Kanban) and tools (Jira/Confluence or equivalent).
• Excellent communication skills—able to align technical and non-technical audiences and drive decisions.

Preferred / Nice-to-Have:

• Retail domain experience (ecommerce, merchandising, inventory, supply chain, pricing/promotions, customer/loyalty).
• Experience applying AI/automation to improve engineering delivery and operations.
• Data governance/compliance experience.
• Familiarity with BI tools (Power BI/Tableau) and semantic layer concepts.
• Certifications: PMP, CSM/PSM, SAFe, Databricks/Snowflake certifications.