Consumer Edge

Consumer Edge

Empowering Global Markets with Unrivaled Consumer Intelligence

Professional Services

Description

  • Lead, mentor, and develop a team of data engineers across three data engineering teams.
  • Own hiring, onboarding, and performance management for the data engineering function.
  • Set technical direction for the GCP-based data platform and its evolution.
  • Own the architecture, reliability, and performance of core data infrastructure, including BigQuery, Cloud Composer/Airflow, Dataflow, Pub/Sub, and GCS.
  • Design and maintain scalable pipelines for ingesting, transforming, and serving alternative datasets.
  • Drive infrastructure best practices across cost optimization, observability, incident response, and disaster recovery.
  • Ensure data security, access controls, and compliance standards for regulated financial services clients.
  • Translate business priorities and client requirements into a technical roadmap.
  • Partner with data operations, data science, product, and commercial teams to accelerate dataset onboarding and expand platform capabilities.
  • Represent data engineering in leadership discussions and contribute to company strategy and data quality standards.

Requirements

  • 10+ years of experience in data engineering, including at least 3 years in a leadership or management role.
  • Experience managing managers and teams.
  • Proven experience building and operating large-scale data pipelines on Google Cloud Platform.
  • Deep expertise with the GCP data stack, including BigQuery, Dataflow, Pub/Sub, GCS, and Cloud Composer.
  • Hands-on experience with dbt Core or dbt Cloud, including modeling patterns, testing frameworks, and documentation standards.
  • Strong understanding of data pipeline design, ELT/ETL patterns, data modeling, and workflow orchestration.
  • Solid grasp of data governance, data quality frameworks, and security best practices.
  • Experience with Terraform and/or Pulumi for infrastructure-as-code provisioning and cloud resource management.
  • Strong proficiency in Python and SQL.
  • Experience in fintech, alternative data, financial data, or another data-as-a-product environment is strongly preferred.
  • Familiarity with alternative data challenges such as diverse formats, inconsistent schemas, high ingestion volumes, and data provenance requirements.
  • Experience supporting data science or ML teams with feature engineering infrastructure is a plus.
  • Familiarity with data licensing, provenance tracking, or data vendor management is a plus.
  • Experience with data mesh or data-as-a-product organizational models is a plus.
  • Open source contributions or published technical work are a plus.

Benefits

  • Annual base salary of $270,000–$300,000, based on experience.
  • Performance-based bonus opportunity.
  • Company equity.
  • 401(k) matching.
  • Subsidized health benefits.
  • Paid parental leave.
  • Flexible and generous time off.
  • Work-from-home flexibility.

Interested in this position?

Apply directly on the company website

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