Lead Data Engineer
WFA Digital Insight
As the demand for data-driven insights continues to skyrocket, with a 25% increase in jobs requiring data engineering skills in 2025, professionals with expertise in Google Ads, Google Analytics, and data management are in high demand. Forbes, a global media powerhouse, is seeking a seasoned Lead Data Engineer to spearhead its data engineering team in India. With a strong technical background and experience in people management, the ideal candidate will thrive in this remote role, which offers a unique blend of technical challenge and leadership opportunity. Before applying, candidates should be aware of the importance of staying up-to-date with the latest developments in data engineering and analytics, as well as the need for excellent communication skills to collaborate effectively with cross-functional teams.
Job Description
About the Role
As a Lead Data Engineer at Forbes, you will play a pivotal role in shaping the company's data engineering strategy and leading a team of talented data engineers. Your day-to-day responsibilities will include managing the delivery of data products, driving engineering excellence, and collaborating with cross-functional teams to ensure seamless integration of data insights into business decision-making. You will be working closely with the analytics, BI, and revenue operations teams to ensure that data engineering efforts are aligned with business objectives.The data engineering team at Forbes is responsible for building and maintaining pipelines that support reporting, analytics, and machine learning use cases. As the Lead Data Engineer, you will be responsible for guiding the technical architecture decisions for these pipelines, ensuring that they are scalable, secure, and compliant with data governance regulations. Your team will be working on a range of exciting projects, from developing data warehousing solutions to implementing machine learning algorithms, and you will be responsible for ensuring that these projects are delivered on time and to a high standard.
What You Will 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 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
- Develop and maintain technical roadmaps for the data engineering team, ensuring alignment with business objectives
- Stay up-to-date with the latest developments in data engineering and analytics, applying this knowledge to drive innovation and improvement in the team
What We Are Looking For
- 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
- Experience with data from Google Ads, Meta, TikTok, Taboola, Outbrain, and Google Analytics (GA4)
- Familiarity with BI tools like Tableau or Looker
Nice to Have
- Experience leading data engineering teams in digital media or performance marketing environments
- Exposure to data contracts, schema versioning, or platform ownership patterns
- Knowledge of data science and machine learning concepts, including experience with ML workflows and experimentation platforms
- Certification in data engineering or a related field
Benefits and Perks
- 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
- Leadership role in a fast-growing global data team inside a globally recognized brand
- Opportunities for professional development and growth
- Access to cutting-edge technologies and tools
- Collaborative and dynamic work environment
- Recognition and reward for outstanding performance
How to Stand Out
- To stand out in this role, be prepared to provide specific examples of your experience with data engineering tools and technologies, such as Google Cloud Platform and dbt.
- When applying, make sure to highlight your ability to communicate complex technical concepts to non-technical stakeholders, as this is a critical aspect of the Lead Data Engineer role.
- Familiarize yourself with Forbes' products and services, and be prepared to discuss how your skills and experience align with the company's goals and objectives.
- Be prepared to discuss your experience with agile methodologies and sprint planning, and how you have applied these principles in previous roles.
- Consider creating a portfolio of your work, including examples of data engineering projects you have led or contributed to, to demonstrate your skills and experience to potential employers.
- When negotiating salary, be sure to research the market rate for Lead Data Engineers in your location, and be prepared to discuss your expectations and requirements.
- Be wary of companies that do not provide clear information about their data engineering team, or that seem to be lacking in transparency or communication - these can be red flags for a potential employer.
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