Data Craftsperson

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.