Lead Analytics Engineer

Overview

Hybrid
Depends on Experience
Contract - W2

Skills

Financial Services
Data Warehouse

Job Details

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 (Google Cloud Platform Composer)

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

  • Other Tools: Google Cloud Platform 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.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

About Gardner Resources Consulting, LLC