Senior Data Engineer

Salary: $120,000-$140,000 yearly salary + benefits (See below for more details)

About us:
Spring Financialis a Canadianfinancial technology companyfocused on making every day financial servicessimpler, faster, and more accessible.
We build technology that helps Canadiansbuild credit, save money, and access lending productswithout unnecessary friction. Our platforms allow customers to apply and manage their financesonline, by text, or over the phone, making the experience convenient and flexible.
Since launching in 2014, Spring has grown into one of Canadas largest fintechs, with over250,000+ product originationsacross credit-building products, personal lending, and mortgage solutions.
Were a fast-growing, product-driven team that valuespractical solutions, strong execution, and thoughtful collaboration. We give people ownership, trust them to make decisions, and focus on building systems that scale reliably.

If youre interested in working onreal-world fintech platforms used by hundreds of thousands of Canadians, Spring offers the opportunity to make a tangible impact through well-built technology.

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 stackAWS-native services, Snowflake, Kafka, Spark/Flink, and orchestration frameworksto 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, and ML feature pipelines into modern infrastructure. Youre 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 engineeringboth 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 youll do:

• Architect and lead delivery of scalable, secure, and reliable data pipelines and platform components across AWS, Snowflake, 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 capabilitieswithin 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, 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!