Senior Data Engineer

Senior Data Engineer at Wellness Living

Location:

Thornhill, Canada

Salary: $120000 - $140000 /year

Job Type: Full-time

Date Posted:
October 28th, 2025

Title:

Senior Data Engineer

Salary: $120,000 - $140,000 + Benefits + Vacation

Location:

Thornhill, Canada (Remote)

Length:
Permanent, full-time

At Wellness Living, we empower thousands of health and wellness business owners to turn their entrepreneurial dreams into reality. Our mission‑critical software fuels their vision, supporting millions of clients around the world in their wellness journeys. With a deep commitment to putting our customers first, we foster a culture that values high performance, adaptability, and accountability. If you are a skilled professional who thrives in a fast‑paced, customer‑focused environment and are passionate about making a meaningful impact on the health and wellness industry, we would love to connect with you.

Our team is driven by four core values that shape everything we do. If you share these values and meet the qualifications outlined for this role, we encourage you to apply - we’d love to learn more about you!

We approach every challenge with a customer‑focused lens, driven by an obsession with our customers’ happiness and success.

We approach every task, whether big or small, with a steadfast commitment to exceptional execution and the pursuit of greatness.

We take full ownership of our decisions, actions, and outcomes – both successes and failures.

We recognize that sustained success demands that we be malleable and purposefully evolve, acknowledging that the world is dynamic and constantly changing.

We’re seeking a seasoned Senior Data Engineer to help lead the modernization of our data infrastructure as we transition from a tightly coupled monolithic system to a scalable, microservices‑based architecture. This role is central to decoupling legacy database structures, enabling domain‑driven service ownership, and powering real‑time analytics, operational intelligence, and AI initiatives across our platform. You will work closely with solution architects and domain owners to design resilient pipelines and data models that reflect business context and support scalable, secure, and auditable data access for internal and external consumers.

• Monolith‑to‑Microservices Data Transition:
  Lead the decomposition of monolithic database structures into domain‑aligned schemas that enable service independence and ownership.
• Pipeline Development & Migration:
  Build and optimize ETL/ELT workflows using Python, PySpark/Spark, AWS Glue, and dbt, including schema/data mapping and transformation from on‑prem and cloud legacy systems into data lake and warehouse environments.
• Domain Data Modeling:
  Define logical and physical domain‑driven data models (star/snowflake schemas, data marts) to serve cross‑functional needs, BI, operations, streaming, and ML.
• Legacy Systems Integration:
  Design strategies for extracting, validating, and restructuring data from legacy systems with embedded logic and incomplete normalization.
• Database Management:
  Administer, optimize, and scale SQL (MySQL, Aurora, Redshift) and No
  
  SQL (Mongo
  
  DB) platforms to meet high‑availability and low‑latency needs.
• Cloud & Serverless ETL:
  Leverage AWS Glue Catalog, Crawlers, Lambda, and S3 to manage and orchestrate modern, cost‑efficient data pipelines.
• Data Governance & Compliance:
  Enforce best practices around cataloging, lineage, retention, access control, and security, ensuring compliance with GDPR, CCPA, PIPEDA, and internal standards.
• Monitoring & Optimization:
  Implement observability (Cloud Watch, logs, metrics) and performance tuning across Spark, Glue, and Redshift workloads.
• Stakeholder
  
  Collaboration:
  
  Work with architects, analysts, product managers, and data scientists to define, validate, and prioritize requirements.
• Documentation & Mentorship:
  Maintain technical documentation (data dictionaries, migration guides, schema specs) and mentor junior engineers in engineering standards.

• Experience:
  
  5+ years in data engineering with a proven record in modernizing…