Lead Analytics Engineer

We’re seeking a Lead Analytics Engineer to help design, model, and scale a modern data environment for a global software organization. The company manages large volumes of data across multiple business units, and this role will play a key part in organizing and maturing that landscape as part of a multi-year strategic roadmap.

This position is ideal for a senior-level analytics engineer who can architect data solutions, build robust models, and stay hands-on with development.

Role Focus

• Architect and build new data models using dbt and modern modeling techniques.

• Partner closely with leadership and business teams to translate complex requirements into technical solutions.

• Support initiatives focused on Finance and Payments data domains.

• Drive structure and clarity within a growing analytics ecosystem.

Technical Environment

• Primary Data Warehouse: BigQuery (mandatory)

• Nice to Have: Snowflake, Redshift

• Orchestration: Airflow (GCP Composer)

• Languages: Expert-level SQL / dbt; strong Python required

• Other Tools: GCP or AWS, Fivetran, Apache Beam, Looker or Preset, Docker

• Modeling Techniques: Vault 2.0, 3NF, Dimensional Modeling, etc.

• Version Control: Git / CI-CD

• Quality Tools: dbt-Elementary, dbt-Osmosis, or Great Expectations preferred

Responsibilities

Business Stakeholder Engagement

• Gather and document complex business requirements.

• Translate business needs into scalable, maintainable data products.

• Serve as a trusted data partner across multiple departments.

Data Modeling & Transformation

• Design and implement robust, reusable data models within the warehouse.

• Develop and maintain SQL transformations in dbt.

• Optimize existing models and queries for performance, cost-efficiency, and maintainability.

Data Pipeline & Orchestration

• Build and maintain reliable data pipelines in collaboration with data engineering.

• Utilize orchestration tools (Airflow) to manage and monitor workflows.

• Manage and support dbt environments and transformations.

Data Quality & Governance

• Implement validation checks and quality controls to ensure data integrity.

• Define and enforce data governance best practices, including lineage and access control.

Enable Data Democratization & Self-Service Analytics

• Curate and prepare datasets for analysts, business users, and data scientists.

• Develop semantic layers for consistent and accessible reporting.

Qualifications

• Bachelor’s degree in Economics, Mathematics, Computer Science, or related field.

• 10+ years of experience in an Analytics Engineering role.

• Expert in SQL and dbt with demonstrated modeling experience (Vault, 3NF, Dimensional).

• Hands-on experience with BigQuery or other cloud data warehouses.

• Proficiency in Python and Docker.

• Experience with Airflow (Composer), Git, and CI/CD pipelines.

• Strong attention to detail and communication skills; able to interact with both technical and business stakeholders.

• Experience in financial services or payments is a plus but not required.