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Lead Data Engineer

Forbes Advisor

Chennai, IndiaRemote3 weeks ago
59 views28 saves7 applies

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Benefits

Parental LeaveWellness Program

Job Type

full time

Description

Forbes Advisor is a high-growth digital media and technology company dedicated to helping consumers make confident, informed decisions about their money, health, careers, and everyday life. We do this by combining data-driven content, rigorous product comparisons, and user-first design — all built on top of a modern, scalable platform. Our teams operate globally and bring deep expertise across journalism, product, performance marketing, and analytics.

The Role

We’re hiring a Data Engineering Lead to help scale and guide a growing team of data engineers. This role is ideal for someone who enjoys solving technical challenges hands-on while also shaping engineering best practices, coaching others, and helping cross-functional teams deliver data products with clarity and speed.

You’ll manage a small team of ICs responsible for building and maintaining pipelines that support reporting, analytics, and machine learning use cases. You’ll be expected to drive engineering excellence — from code quality to deployment hygiene — and play a key role in sprint planning, architectural discussions, and stakeholder collaboration.

This is a critical leadership role as our data organization expands to meet growing demand across media performance, optimization, customer insights, and advanced analytics.

What you’ll do

  • Lead and grow a team of data engineers working across ETL/ELT, data warehousing, and ML-enablement
  • Own team delivery across sprints, including planning, prioritization, 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 optimization needs
  • Ensure data security, compliance, and scalability — especially around first-party customer data
  • Mentor junior engineers through code reviews, pairing, and technical roadmap discussions

What You Bring

  • 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 modeling 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

Why Join Us

  • Monthly long weekends — every third Friday off
  • Wellness reimbursement to support your health and balance
  • Paid parental leave
  • Remote-first culture with flexibility and trust

This job is found at InterviewStack.io

Skills

analyticsmachine learningetldata warehousingobservabilitygcpbigquerydbtsqlscalabilitypythonsparkkafkaairflowagiletableaulookergoogle adsgoogle analyticsdata privacyexperimentationcode reviewteam leadershippeople management

About Forbes Advisor

Forbes Advisor is a global platform dedicated to helping consumers make the best financial choices for their individual lives.

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