Senior Data Engineer

Spellbook

23d•CA$140,000 - CA$210,000

About The Position

Spellbook is seeking a Senior Data Engineer to join our growing team. In this role, you’ll lead the design and development of scalable data infrastructure that powers both internal analytics and AI-driven product capabilities, helping transform large volumes of contract data into actionable market insights. You’ll build reliable, compliant, and extensible systems that accelerate product development and support the next stage of Spellbook’s growth. As a Senior Data Engineer, you’ll play a key role in shaping the future of Spellbook’s data platform. You’ll operate at the intersection of data engineering, infrastructure, and product strategy, with broad ownership across architecture, execution, and long-term platform evolution.

Requirements

You have 5+ years of experience in Infrastructure Engineering or Data Platform Engineering.
You have exceptional communication skills. You can explain and advocate your ideas to a diverse audience, and you document architectural decisions clearly.
You can take an ambiguous, high-impact platform requirement from a vague abstract idea, to a working prototype, to a production-ready system deployed to serve internal teams and unblock product delivery.
You are a self-starter and problem-solver motivated by curiosity and a desire to help others succeed, encouraged by continuous improvement.
You are a team player who is motivated to help Spellbook succeed. When things break you are eager and able to help fix them. You think of and implement ways to improve the work of the team as a whole.
You have a firm grasp of cloud infrastructure, distributed systems, and relevant security/compliance considerations, and can reason clearly about tradeoffs in cost, reliability, and simplicity.
You have the ability to break complex and vague requirements down into clear achievable enhancements that ship in record time.

Nice To Haves

Experience with workflow orchestration tools (e.g. Dagster, Airflow, Prefect)
Experience working with data warehouses or lakehouses (e.g. Athena, Iceberg, Snowflake)
Experience supporting machine learning workflows (e.g. dataset generation, experimentation, model pipelines)
Experience designing and implementing deletion and retention systems with auditable processes (SOC2-aligned)
Experience integrating product analytics data into a warehouse

Responsibilities

Work as part of a distributed team to identify and implement impactful improvements to the company’s data platform, accelerating product and AI development
Design, architect and implement scalable data infrastructure supporting both analytics and AI/ML-driven product features.
Build and maintain compliant, auditable data storage and processing systems in AWS, with infrastructure-as-code.
Develop and operate robust data pipelines and orchestration systems and own the generation of core datasets, ensuring they are reliable, reproducible and easy to evolve, with robust backfill and reprocessing capabilities
Designing and implementing data retention and deletion workflows that meet legal and compliance requirements
Contribute to architectural decisions and documentation as the platform evolves
Other responsibilities as required.