Data Engineer - Financial Data Platform

Spotify; Toronto; Hybrid; CAD 80,000 - 130,000; Full time

Job summary

An innovative firm is seeking engineers to shape the future of financial data. In this role, you will design scalable data pipelines, manage the full data product lifecycle, and collaborate with cross-functional teams to build reliable data products. This position offers the chance to work with complex financial domains and contribute to impactful projects that drive strategic decisions. With a focus on quality and collaboration, you will thrive in a flexible environment that values your insights and expertise. If you are passionate about data and eager to make a difference, this opportunity is perfect for you.

Qualifications

• Experience with data processing frameworks and cloud environments.
• Strong analytical skills and data modeling capabilities.

Responsibilities

• Build scalable data pipelines processing billions of records.
• Collaborate with teams to create flexible, intuitive data products.

Skills

Data Processing Frameworks (Flink, Beam, Dataflow, Spark)

Cloud-based Environments (Google Cloud Platform)

SQL

Data Modeling

Analytical Skills

Clean Code Practices

Collaboration

Job description

At Spotify, Financial Engineering is building the platform that powers Finance and enables strategic decision-making across the company. Our mission is to create trusted financial abstractions that make complexity manageable and insight actionable — supporting everything from premium and ads growth to forecasting, experimentation, and global reporting.

As engineers in the Financial Data Platform team, we turn messy, fragmented realities into clean, reusable foundations. We build core datasets that represent key financial domains like Premium, Ads, and Royalties. We create libraries and tools that empower others to produce and trust financial data at scale. We collaborate deeply with Finance, Product, and Data teams to unlock clarity and drive Spotify’s ambitions forward.

We are looking for engineers who are excited to shape the future of financial data at Spotify. You will design and operate scalable pipelines that process billions of records. You will apply product thinking to financial data — managing the full lifecycle from sourcing to documentation to exposure. You will define abstractions that simplify complexity and create intuitive paths for our consumers. Together, we advocate for standards, champion quality, and build systems that others can rely on with confidence.

If you thrive on building foundations that have broad, lasting impact, and want to work where financial data truly drives strategy, we’d love to work with you.

What You'll Do

• Acquire a comprehensive understanding of how financial data supports diverse consumer needs, from Finance to broader business customers.
• Build core datasets and financial abstractions that serve as sources of truth for strategic and operational decision-making.
• Design, prototype, and build scalable data pipelines that process billions of data points reliably.
• Apply product thinking to data: manage the full data product lifecycle from sourcing to documentation and exposition, always prioritizing consumer needs and success.
• Advocate for and implement effective data quality, engineering standards, and reusability.
• Collaborate closely with engineers, data scientists, finance collaborators, and business teams to build flexible, intuitive data products.
• Define data models and abstractions that simplify access to complex financial domains like Premium, Ads, and Royalties.
• Contribute to building tools and libraries that enable other teams to build financial data products at scale.
• Leverage mentorship and constructive feedback to foster accountability, growth, and collaboration within the team.

Who You Are

• Experienced with Data Processing Frameworks: Skilled with higher-level JVM-based frameworks such as Flink, Beam, Dataflow, or Spark.
• Comfortable with Ambiguity: Able to work through loosely defined problems and thrive in autonomous team environments.
• Skilled in Cloud-based Environments: Proficient with large-scale data processing in cloud environments, preferably with experience in Google Cloud Platform.
• Strong Analytical Skills: Adept at breaking down complex problems and communicating insights effectively.
• Knowledgeable About Data Modeling: You treat data as a product, with strong data modeling capabilities.
• Passionate About Clean Code: Committed to writing high-quality, maintainable code and building robust data pipelines.
• Curious and Inquisitive: You have a deep curiosity about data and systems, always seeking to understand and improve them.
• Skilled in large-scale data processing: Comfortable working with SQL and platforms like BigQuery.
• Excellent Collaborator: You value positive relationships across technical and business domains.

Where You'll Be

• This role is based in Toronto, Canada
• We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.