Data Engineer II

Job Description

Job Description

Salary : $100,000-$120,000 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 Data Engineer II at Spring, you are an experienced builder who takes ownership of the pipelines and platforms that power analytics, operational reporting, machine learning, and real-time product features. You work confidently across batch and streaming architectures, using tools like Airflow, Spark, Glue, Kinesis, and Kafkawhile also integrating with Snowflake, and AWS-native services.

Your work extends beyond implementation : you help shape pipeline architecture, evaluate trade-offs between latency and scalability, and ensure data is available, reliable, and usable for a variety of internal stakeholders. You understand how to optimize data structures for analytical queries, power feature stores for ML models, and deliver reproducible workflows across test and production environments.

Youre responsible for designing and delivering full-stack data workflows across ingestion, transformation, validation, and observability. You build durable, testable code in Python and SQL, and leverage infrastructure-as-code and CI / CD practices to manage deployment and change. You use AI tools to speed up routine development, identify potential issues early, and assist in testing and documentationwhile maintaining a critical eye for correctness and security.

You work directly with stakeholders from Data Science, BI, Finance, and Product, translating business and analytical needs into technical deliverables. You help clarify scope, identify technical constraints, and proactively communicate trade-offs and timelines. You also mentor junior engineers, review designs, and raise the teams bar for quality and ownership.

What youll do :

• Design, implement, and maintain secure and scalable pipelines across AWS (e.g., Glue, Lambda, Step Functions), Snowflake, and streaming platforms like Kafka or Kinesis
• Develop and optimize data models, schemas, and transformations to support downstream analytics, ML, and reporting
• Operate orchestration tools such as Airflow to coordinate complex workflows and manage SLAs
• Use AI tools to assist with coding, test scaffolding, data profiling, and documentationensuring results are validated and safe
• Collaborate directly with BI, ML, and Finance teams to clarify requirements and deliver business-impacting solutions
• Troubleshoot and resolve issues in production pipelines, improving system observability, data quality checks, and alerting
• Mentor junior engineers and contribute to team design reviews, engineering practices, and technical planning

Requirements :

What We Will Give You :

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!