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Spring Financial

Senior Data Engineer

Posted 13 Hours Ago
Be an Early Applicant
In-Office
Vancouver, BC
Senior level
In-Office
Vancouver, BC
Senior level
The Senior Data Engineer is responsible for architecting and delivering scalable data infrastructure and pipelines while collaborating across teams, integrating AI capabilities, and mentoring other engineers.
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About us:

Spring Financial is revolutionizing financial access for Canadians, providing smart credit-building, mortgage, and lending solutions. Millions struggle with high-interest debt and limited financial options—we’re here to change that.
As one of Canada’s fastest-growing fintech companies, annually we help 1 million customers explore their financing options with ease—online, via text, or over the phone. Our dynamic, innovative team thrives on collaboration, growth, and making a real impact.
To learn more about our products please visit our website here: www.springfinancial.ca.

NOTE: This is a full-time, permanent, hybrid position in downtown Vancouver. 3 set days in the office and 2 WFH.

Job Overview:

As a Senior Data Engineer at Spring, you are a technical leader and strategic problem-solver who architects high-impact, resilient, and scalable data infrastructure. You work across a diverse stack—AWS-native services, Snowflake, DB2, Kafka, Spark/Flink, and orchestration frameworks—to deliver pipelines and data platforms that are secure, observable, and aligned with business needs.

You own the design and execution of complex data initiatives, such as real-time event platforms, secure data sharing mechanisms, ML feature pipelines, and integration of legacy DB2 systems into modern infrastructure. You’re skilled at navigating ambiguity, balancing trade-offs between speed and sustainability, and ensuring that our data architecture scales with the business.

You are an advocate for AI-augmented engineering—both in how you and your team build (e.g., using AI for testing, schema discovery, and code generation), and in what the platform enables (e.g., semantic tagging, automated QA, natural language interfaces). You model responsible AI usage and help others incorporate it thoughtfully into development workflows.


You work across teams to frame problems, define SLAs, manage risk, and align data architecture with business goals. You are a trusted partner to senior stakeholders across Finance, Risk, Product, Analytics, and Engineering, and you influence both platform strategy and organizational standards. You also coach other engineers, lead architectural design reviews, and help set the technical direction for the team.
What you’ll do:

  • Architect and lead delivery of scalable, secure, and reliable data pipelines and platform components across AWS, Snowflake, DB2, and streaming systems (Kafka, Flink, etc.)
  • Scope and drive strategic initiatives to modernize legacy data flows, unify batch and streaming sources, and enable cross-functional self-serve analytics
  • Champion the integration of AI capabilities—within data pipelines (e.g., anomaly detection, tagging) and within development practices (e.g., assisted testing, documentation)
  • Collaborate with technical and business leaders to clarify ambiguous problems, assess risks, and propose scalable, extensible solutions
  • Define and enforce engineering standards around testing, observability, security, and CI/CD within data systems
  • Lead technical design and code reviews, mentor engineers across levels, and support the ongoing evolution of our data architecture
  • Partner with ML, Analytics, and Finance teams to deliver data with appropriate latency, accuracy, and governance for their use cases

Requirements:

  • Expertise in designing and scaling data pipelines using Snowflake, DB2, and AWS-native tools (e.g., Glue, Lambda, Redshift, Step Functions)
  • Strong experience with real-time data systems, including Kafka, Kinesis, Flink, or Spark Streaming
  • Deep knowledge of data modeling, schema evolution, privacy-preserving design, and secure data architectures
  • Fluency in Python and SQL; proficiency with infrastructure-as-code (e.g., Terraform or CDK)
  • Track record of embedding AI into both platform functionality and development workflows
  • Proven ability to align data engineering with business value, and to lead cross-functional initiatives from concept through delivery
  • Excellent communication and collaboration skills; trusted advisor across engineering and business teams
  • Demonstrated ability to mentor and influence engineers, set standards, and guide technical direction

What We Will Give You: 

  • Competitive annual salary ranging from $120,000 to $140,000, reflective of experience and impact.
  • Comprehensive benefits package, including extended health, dental, and vision coverage — with 100% of monthly premiums covered by the Spring.
  • GRSP matching program to support your long-term financial goals.
  • Transit-Friendly Employer (Transit allowance).
  • A modern, collaborative workspace in the heart of downtown Vancouver.
  • Ongoing career growth opportunities

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Please note: Upon applying, our Talent Acquisition team will review your resume. If you qualify, we will reach out to learn more about your experience and answer any questions you may have about the role, benefits, compensation, and more. Due to high application volume, we may not be able to respond to everyone.

Thank you for your interest! We appreciate your time and look forward to reviewing your application!

Top Skills

AWS
Cdk
Db2
Flink
Glue
Kafka
Lambda
Python
Redshift
Snowflake
Spark
SQL
Step Functions
Terraform
HQ

Spring Financial Vancouver, British Columbia, CAN Office

505-555 Burrard St., #600, Vancouver, British Columbia, Canada, V7X 1M8

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