The Data Engineer will own the design, development, and optimization of the data infrastructure that underpins analytics, reporting, and machine learning initiatives across the credit union. Working closely with business intelligence analysts, compliance teams, and technology leadership, this role requires both technical depth and the ability to translate complex data challenges into reliable, scalable solutions within a regulated financial environment.

ESSENTIAL FUNCTIONS AND BASIC DUTIES

Architect, build, and maintain robust ETL/ELT pipelines to integrate data from core banking systems, lending platforms, digital banking channels, and third-party vendors

Design and manage the credit union’s data warehouse and data lake, including schema design, partitioning strategies, and performance optimization

Develop and enforce data quality frameworks, including automated testing, validation rules, and alerting for pipeline anomalies

Lead the implementation of data modeling best practices (dimensional modeling, data vault, or similar) to support scalable analytics

Collaborate with data analysts, compliance officers, and business stakeholders to define data requirements and deliver trusted data products

Manage orchestration and scheduling of data workflows using tools such as Matillion, Snowflake, or equivalent

Evaluate, implement, and maintain cloud data infrastructure on Snowflake or Azure, including compute, storage, and networking resources

Ensure all data processes comply with applicable regulations, including NCUA guidelines, BSA/AML requirements, and GLBA data privacy standards

Partner with the IT security team to enforce data access controls, encryption standards, and audit logging

Mentor junior data engineers and analysts, providing technical guidance and code reviews

Drive adoption of DataOps practices, including CI/CD for data pipelines, version control, and documentation standards

Support data migration efforts during platform transitions, core system upgrades, or mergers and acquisitions





Works a regular and predictable schedule.

QUALIFICATIONS
REQUIRED QUALIFICATIONS

Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field (or equivalent professional experience)

3–5 years of hands‑on experience in data engineering, data infrastructure, or a closely related role

Advanced proficiency in SQL and experience with large‑scale relational and columnar databases (e.g., PostgreSQL, Redshift, Snowflake, BigQuery)

Strong Python skills for data pipeline development and automation

Demonstrated experience designing and maintaining ETL/ELT workflows using tools such as dbt or Matillion

Working knowledge of at least one major cloud platform (Snowflake, AWS, Azure, or GCP) and associated data services

Solid understanding of data warehousing concepts including dimensional modeling and schema design

Experience implementing data quality monitoring, lineage tracking, and observability practices

Strong communication skills with the ability to work effectively across technical and non‑technical audiences

PREFERRED QUALIFICATIONS

Experience in a regulated financial services environment such as credit unions, banks, or fintech companies

Familiarity with credit union core banking platforms such as Symitar (Episys), Jack Henry, or FiServ

Knowledge of data governance frameworks, or master data management

Exposure to machine learning pipelines and feature engineering for predictive models

Experience with BI platforms such as Power BI, Tableau, or Looker

Relevant certifications such as AWS Certified Data Analytics, Snowflake SnowPro, or dbt Certified Developer

Familiarity with NCUA examination processes or financial regulatory reporting (e.g., HMDA, Call Report data)

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Equal Chance Employer

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📌 Data Engineer (British Columbia)
🏢 Love Where You Work
📍 British Columbia