Lead Data Engineer

Forbes • Publishing • Digital Media • Python • SQL • Tableau • ETL/ELT • Looker • 2 days ago
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Salary
≈ $29k – $63k per year (Estimated)
Location
Remote (India)
Seniority
Staff · 7+ years exp

First seen by Alion on Oct 24, 2026. Forbes scores A on the Alion truth index.

Overview
Company
Impact
Profile match

Forbes

Forbes is a leading global media and branding company that focuses on business, investing, technology, entrepreneurship, leadership, and luxury lifestyle. It is widely recognized for its high-profile journalism, in-depth financial analysis, and influential lists, such as the Forbes 400 and the 30 Under 30, which track wealth and achievement worldwide. Through its digital platform and print publications, the organization provides news and insights that empower business leaders, investors, and entrepreneurs to succeed in a changing global economy.
forbes.com • HQ: Jersey City, United States • Digital Media • Financial News & Media • Publishing • 51-200 employees • Est. 1917
Tech stack of Forbes

Responsibilities:

  • Lead and grow a team of data engineers working across ETL/ELT, data warehousing, and ML-enablement.
  • Own team delivery across sprints, including planning, prioritisation, QA, and stakeholder communication.
  • Set and enforce strong engineering practices around code reviews, testing, observability, and documentation.
  • Collaborate cross-functionally with Analytics, BI, Revenue Operations, and business stakeholders in Marketing and Sales.
  • Guide technical architecture decisions for our pipelines on GCP (BigQuery, GCS, Composer).
  • Model and transform data using dbt and SQL, supporting reporting, attribution, and optimisation needs.
  • Ensure data security, compliance, and scalability, especially around first-party customer data.
  • Mentor junior engineers through code reviews, pairing, and technical roadmap discussions.


Requirements:

  • 6+ years of experience in data engineering, including 2+ years of people management or formal team leadership.
  • Strong technical background with Python, Spark, Kafka, and orchestration tools like Airflow.
  • Deep experience working in GCP, especially BigQuery, GCS, and Composer.
  • Strong SQL skills and familiarity with DBT for modelling and documentation.
  • Clear understanding of data privacy and governance, including how to safely manage and segment first-party data.
  • Experience working in agile environments, including sprint planning and ticket scoping.
  • Excellent communication skills and proven ability to work cross-functionally across global teams.


Nice to have:

  • Experience leading data engineering teams in digital media or performance marketing environments.
  • Familiarity with data from Google Ads, Meta, TikTok, Taboola, Outbrain, and Google Analytics (GA4).
  • Exposure to BI tools like Tableau or Looker.
  • Experience collaborating with data scientists on ML workflows and experimentation platforms.
  • Knowledge of data contracts, schema versioning, or platform ownership patterns.

Skills

airflow, apache airflow, data, kafka, python, spark

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