Lead GCP Analytics Engineer

3 days ago

Boston, Massachusetts, United States Hatch Pros Full time $120,000 - $200,000 per year

GC Holder or US Citizens
need Local and LinkediN profile

Key Skills:
GCP, SQL, Python, financial payment processing project preferred

We're seeking a Lead Analytics Engineer to help design, model, and scale a modern data environment for a global payment processing 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 lead-level analytics engineer who can architect data solutions, build robust models, and stay hands-on with development.

Qualifications

  • 10+ years of experience in an Analytics Engineering role.
  • Lead-level resource to help with design and architecture
  • 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.
  • Bachelor's degree in Economics, Mathematics, Computer Science, or related field.

Role Focus

  • Architect and build new GCP 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: Google 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.

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