Data Engineer II

Job Description

Job Description

Salary : $100,000-$120,000 yearly salary + benefits (See below for more details)

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 optionswere here to change that.

As one of Canadas fastest-growing fintech companies, annually we help 1 million customers explore their financing options with easeonline, 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 : .

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!