Data Engineer

Responsedga Technology And Marketing Inc.

New York (NY)

On-site

USD 90,000 - 120,000

Full time

14 days+
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Job summary

A leading growth marketing firm in New York is seeking a Data Engineer to design and maintain first-party data infrastructure. The role involves building data pipelines, ensuring data quality, and creating finance-grade reporting. Candidates should have over 3 years of experience in data engineering, strong SQL skills, and proficiency in using BigQuery, dbt, and Airflow. Join our team to help shape the future of growth marketing in a collaborative environment.

Qualifications

  • 3+ years in data engineering with BigQuery, dbt, or equivalent stack.
  • Experience building and maintaining production data pipelines.
  • Strong SQL skills and understanding of data modelling best practices.

Responsibilities

  • Designing and maintaining first-party data infrastructure.
  • Developing data pipelines for ingestion, transformation, and quality assurance.
  • Creating finance-grade reporting tables as the single source of truth.
  • Monitoring data quality and responding to incidents.

Skills

Data engineering
BigQuery
SQL
Data pipeline development

Tools

dbt
Airflow
Looker

Job description

You build the measurement spine of Growth OS. Using BigQuery, dbt, Airflow, and Looker, you design, maintain, and scale the first-party data infrastructure. You transform raw data from ad platforms into finance-grade, decision-ready tables. You are the architect of the single source of truth that both CFO and CMO trust.

What you'll operate:
  • First-party data infrastructure design using BigQuery, dbt, and Airflow
  • Data pipeline development: ingestion, transformation, and quality assurance
  • Finance-grade reporting tables that serve as the single source of truth
  • Data quality monitoring and incident response
What the system requires:
  • 3+ years in data engineering with BigQuery, dbt, or equivalent stack
  • Experience building and maintaining production data pipelines
  • Strong SQL skills and understanding of data modelling best practices
  • You build the infrastructure that makes data trustworthy — not just available.
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