Description:

We are seeking a Senior Data Platform Engineer to design and build scalable, data-intensive applications.
This role requires expertise in ingesting and transforming large datasets, creating APIs for efficient data retrieval, and developing data products that drive business insights.
You will be a key player in shaping our data platform while contributing to backend engineering initiatives.
The ideal candidate bridges the gap between traditional data engineering and backend development, building ETL pipelines, APIs, and data-driven solutions with a focus on performance and scalability.
Key responsibilities include designing and implementing ETL pipelines capable of processing terabytes of credit data efficiently, developing and optimizing APIs for fast and reliable data retrieval, architecting and managing scalable storage solutions, collaborating with teams to turn raw data into actionable products, performing data analysis, working closely with stakeholders, and documenting processes while mentoring junior engineers.

Requirements:

A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field is required.
The candidate must have 5+ years of experience in backend or data engineering roles.
Proven experience building APIs for data access and processing large-scale datasets is necessary.
Familiarity with credit or financial data and related compliance considerations is preferred.
Expertise in a modern programming language such as Go, Python, or Java is essential.
Strong knowledge of database systems (SQL and NoSQL), focusing on scalable solutions like Bigtable, BigQuery, or DynamoDB is required.
A deep understanding of API design principles and best practices for performance and scalability is necessary.
Familiarity with cloud platforms (AWS, GCP, or Azure) and associated data services is important.
Experience with containerization (Docker, Kubernetes) and CI/CD pipelines is required.
Strong analytical and problem-solving skills, excellent communication skills, and the ability to work collaboratively in a fast-paced environment are essential.
Nice to have: Proficiency with data processing tools (e.g., Apache Beam, Spark, Flink), knowledge of data product lifecycle management, experience with schema design and managing data integrity in distributed systems, and familiarity with modern monitoring and observability tools.

Generous compensation in cash and equity is offered.
Early exercise for all options, including pre-vested, is available.
The company promotes a remote-first culture, allowing employees to work from anywhere.
Flexible paid time off, a year-end break, and self-care days off are provided.
Health insurance, dental, and vision coverage for employees and dependents is available for US and Canada specific employees.
A 4% matching in 401k / RRSP is offered for US and Canada specific employees.
A MacBook Pro will be delivered to your door.
A one-time stipend to set up a home office, including desk, chair, screen, etc., is provided.
Monthly meal stipend and monthly social meet-up stipend are included.
An annual health and wellness stipend and an annual learning stipend are offered.
Unlimited access to an expert financial advisory is available.