Data Craftsperson

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Craftsperson based in Canada.

This is an opportunity for a data-focused engineer who takes pride in building clean, reliable, and well-tested data solutions.

You’ll work primarily across data engineering, with an analytics component that connects technical work directly to business needs.

The role provides hands-on ownership across data pipelines, cloud infrastructure, data modeling, analytics, and production support.

You’ll work with modern technologies including SQL, Python, Snowflake, and Azure cloud services while following strong engineering practices.

The environment emphasizes Extreme Programming principles, collaboration, continuous learning, and technical craftsmanship.

You’ll also have opportunities to work directly with stakeholders and contribute throughout the complete delivery lifecycle.

This role is well suited to a detail-oriented data professional who enjoys solving complex problems and continuously improving how data is built and used.

Accountabilities

• Design, build, maintain, and improve reliable data pipelines and infrastructure using SQL and Python.
• Develop and optimize data models in Snowflake or equivalent cloud data warehouses to support business and analytics requirements.
• Parse, transform, and process structured and semi-structured data, including JSON and XML, from a variety of sources.
• Diagnose and resolve issues across raw, intermediate, and summary data layers.
• Develop repeatable SQL-based analytics solutions based on stakeholder requirements and business use cases.
• Investigate and resolve data quality issues, including urgent and time-sensitive production problems.
• Identify opportunities to simplify and consolidate data models while maintaining a reliable single source of truth.
• Support data infrastructure and cloud environments, contributing to reliable end-to-end data operations.
• Apply strong testing, refactoring, version control, and continuous integration practices to maintain high-quality solutions.
• Collaborate with developers, stakeholders, and client teams throughout the delivery lifecycle, taking ownership from development through release and support.
• Contribute to analytics activities, leveraging data engineering expertise to help stakeholders derive meaningful insights.

Requirements

• 2+ years of experience with SQL and relational databases, including the ability to understand complex data relationships, transformations, and dependencies.
• 2+ years of experience with Python for data engineering or related technical data workflows.
• Professional experience with Snowflake or another modern cloud data warehouse.
• Working knowledge of Azure cloud services, particularly Azure Data Factory, Azure Blob Storage, and Azure SQL Database.
• Knowledge of Git and modern version control practices.
• Strong attention to data quality, accuracy, consistency, and detail.
• Ability to investigate technical problems methodically and communicate findings clearly.
• Familiarity with JSON and XML parsing and processing is a plus.
• Experience with data infrastructure and modeling tools such as dbt and Fivetran is advantageous.
• Exposure to Power BI or other business intelligence tools is beneficial, although analytics is not the primary focus of the role.
• Knowledge of Docker, Linux, Shell/Bash, and virtualization technologies is a plus.
• Familiarity with SSIS packages is advantageous.
• Understanding of CI/CD methodologies and modern DevOps practices.
• Comfortable working in a collaborative engineering environment that values pairing, refactoring, experimentation, continuous learning, and technical excellence.
• Strong ownership mindset and willingness to contribute across the broader data engineering and delivery lifecycle.

Benefits

• Remote-first work environment with structured flexibility and shared core working rhythms.
• Twice-yearly in-person coworking sprints and an annual company retreat, with travel expenses covered.
• Dedicated learning and development budget.
• Sponsorship opportunities for conference talks.
• Comprehensive medical and term insurance.
• Employee-friendly leave policies.
• Home office fund to support an effective remote workspace.
• Collaborative engineering culture centered on pairing, refactoring, experimentation, and continuous improvement.
• Opportunities to work with modern data, cloud, and AI technologies.
• Strong focus on professional growth and lifelong learning.