Lead Analytics Engineer

This is a senior technical leadership role focused on building a reliable, scalable, and well-governed analytics ecosystem.
You will set technical direction for the analytics engineering team while remaining closely connected to business priorities.
The role combines data architecture, analytics engineering, software development practices, and stakeholder partnership.
You will shape data models, semantic definitions, testing standards, and self-service analytics capabilities.
You’ll work cross-functionally with Product, Finance, Marketing, and Engineering to translate business needs into actionable data initiatives.
The position also offers the opportunity to mentor engineers, lead major technical migrations, and improve the operational reliability of the analytics platform.
It is well suited to an experienced data professional who enjoys technical ownership, proactive problem-solving, and enabling others to do their best work.

• 8+ years of professional experience working with data in a software engineering or technology environment.

• Advanced proficiency in SQL and Python, with the ability to build and maintain production-quality analytical systems.

• Strong experience designing and managing business semantic layers, data catalog solutions, and data integrity or testing frameworks.

• Hands-on experience with dbt, including orchestration, modeling practices, and scalable analytics engineering workflows.

• Strong knowledge of relational databases and modern analytical data architectures.

• Experience with DAG-based orchestration tools such as Dagster or Airflow.

• Professional experience with Tableau or comparable business intelligence and visualization platforms.

• Experience working with cloud infrastructure, particularly AWS or GCP, and infrastructure-as-code tools such as Terraform.

• Familiarity with document, graph, or schema-less databases is an advantage.

• Demonstrated ability to work autonomously, proactively identify opportunities, and solve complex data-system challenges.

• Strong understanding of analytics engineering, data architecture, data quality, and business intelligence practices.

• Experience establishing engineering standards such as code review processes, design reviews, automated testing, version control, and maintainable development workflows.

• Strong communication and stakeholder-management skills, with the ability to explain technical concepts clearly and negotiate scope effectively.

• Demonstrated experience mentoring engineers and raising technical standards across a team.