As a Data Engineering Lead at Forbes Advisor, you will play a crucial role in scaling and guiding a team of data engineers. Your responsibilities will include managing a team of individual contributors (ICs) who are responsible for building and maintaining pipelines to support reporting, analytics, and machine learning use cases. It will be essential for you to drive engineering excellence by ensuring code quality, deployment hygiene, and actively participating in sprint planning, architectural discussions, and stakeholder collaboration. **Role Overview:**
In this role, you will lead and grow a team of data engineers, own team delivery across sprints, enforce strong engineering practices, collaborate cross-functionally with various teams, guide technical architecture decisions, model and transform data, ensure data security and compliance, and mentor junior engineers. **Key Responsibilities:**
Lead and grow a team of data engineers specializing in 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, Marketing, and Sales teams
Guide technical architecture decisions for pipelines on GCP (BigQuery, GCS, Composer)
Model and transform data using dbt and SQL for reporting, attribution, and optimization needs
Ensure data security, compliance, and scalability, particularly around first-party customer data
Mentor junior engineers through code reviews, pairing, and technical roadmap discussions
**Qualifications Required:**
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 management of first-party data
Experience in agile environments, including sprint planning and ticket scoping
Excellent communication skills and ability to work cross-functionally across global teams
This is a leadership role within a fast-growing global data team at Forbes Advisor, offering benefits such as monthly long weekends, wellness reimbursement, paid parental leave, a remote-first culture, and the opportunity to work inside a globally recognized brand. As a Data Engineering Lead at Forbes Advisor, you will play a crucial role in scaling and guiding a team of data engineers. Your responsibilities will include managing a team of individual contributors (ICs) who are responsible for building and maintaining pipelines to support reporting, analytics, and machine learning use cases. It will be essential for you to drive engineering excellence by ensuring code quality, deployment hygiene, and actively participating in sprint planning, architectural discussions, and stakeholder collaboration. **Role Overview:**
In this role, you will lead and grow a team of data engineers, own team delivery across sprints, enforce strong engineering practices, collaborate cross-functionally with various teams, guide technical architecture decisions, model and transform data, ensure data security and compliance, and mentor junior engineers. **Key Responsibilities:**
Lead and grow a team of data engineers specializing in 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, Marketing, and Sales teams
Guide technical architecture decisions for pipelines on GCP (BigQuery, GCS, Composer)
Model and transform data using dbt and SQL for reporting, attribution, and optimization needs
Ensure data security, compliance, and scalability, particularly around first-party customer data
Mentor junior engineers through code reviews, pairing, and technical roadmap discussions
**Qualifications Required:**
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 management of first-party data
Experience in agile environments, including sprint planning and ticket scoping
Excellent communication skills and ability to work cross-functionally across global teams
