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Senior Analytics Engineer

Job description

We are looking for a Senior Analytics Engineer to join our collaborative and fast-paced team, helping clients build scalable, trusted, and business-focused data platforms.

In this role, you'll bridge the gap between data engineering and business analytics by designing robust data models, enabling self-service analytics, and ensuring high-quality data is available for decision-making. You'll work closely with our leadership team (CEO/COO), clients, and cross-functional teams to translate business requirements into scalable data solutions.

We're looking for someone who enjoys solving complex data challenges, takes ownership, and is passionate about building modern analytics capabilities while mentoring others and sharing knowledge across the team.

National and international travel may be required depending on project, client, and organizational needs (estimated 0–15%).

How You'll Contribute

  • Design and maintain data models that support analytics, reporting, self-service BI, and operational decision-making.
  • Develop scalable SQL transformations using modern analytics engineering best practices, ensuring reusable, maintainable, and high-performing datasets.
  • Build and manage analytics transformation pipelines using dbt, SQLMesh, or similar modern data transformation frameworks.
  • Improve data quality by implementing testing, documentation, monitoring, and governance across the analytics layer.
  • Partner with business stakeholders to understand analytical requirements and translate them into scalable data models and trusted metrics.
  • Contribute to modern data architecture, helping evolve semantic layers, metrics definitions, and reusable data assets.
  • Enable AI and advanced analytics use cases by designing data models and metadata that support AI/ML and LLM-powered applications.
  • Mentor team members by promoting engineering best practices, knowledge sharing, and continuous improvement.


Requirements

  • Strong SQL skills with a SQL-first approach to data modelling and analytics.
  • Experience designing and implementing scalable data models.
  • Hands-on experience with dbt, SQLMesh, or similar data transformation frameworks.
  • Experience working with cloud data warehouses such as Snowflake, BigQuery, or Redshift.
  • Solid understanding of modern data architecture and data warehousing best practices.
  • Ability to understand business requirements and translate them into robust data solutions.
  • Strong understanding of data modelling trade-offs, balancing performance, maintainability, and flexibility.
  • Experience with semantic layers, metrics layers, or self-service analytics platforms.
  • Experience designing data models to support AI/ML or LLM-powered applications is a plus.
  • Strong collaboration and communication skills, with experience working in cross-functional teams.


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