As a Lead Analytics Engineer at MANUAL, you will be at the forefront of our data infrastructure, transforming raw data into a scalable foundation for actionable insights. You will own the design, development, and optimisation of data models that empower the business to make data-driven decisions. Collaborating with cross-functional teams, you will bridge the gap between raw data and meaningful analytics, ensuring that our modern data stack supports our strategic goals.
This role demands a deep understanding of both technical and business contexts, ensuring that data solutions align with company objectives. You will play a critical role in shaping our data culture and enabling a high-performing analytics function.
We leverage the modern data stack, including industry-leading tools such as BigQuery, dbt, and Looker, to create a powerful and efficient analytics ecosystem.
Responsibilities
Team Leadership: Lead a team of Analytics Engineers and Analysts, setting priorities, mentoring team members, and delivering impactful solutions collaboratively.
Data Modeling Ownership: Architect, maintain, and optimize the core data models and transformations that underpin our analytics capabilities. Build scalable and performant data models to meet the organization’s needs.
Collaboration: Work closely with teams across marketing, finance, operations, and product to understand business requirements and translate them into robust technical solutions.
Data Governance: Ensure data integrity, consistency, and security while maintaining documentation and implementing best practices across the analytics ecosystem.
Experience: 7+ years in data engineering, analytics engineering, or a related role.
Technical Expertise: Advanced SQL skills and proficiency in a scripting language (e.g., Python).
Data Modeling Mastery: Hands-on experience with dbt or Dataform, and the ability to design and optimize scalable data models.
Analytical Acumen: Strong understanding of approaches to measurement, data analysis, and statistics.
