Lead Data Engineer

Role Overview:

You are being hired as a Data Engineering Lead to support and guide a growing team of data engineers. Your responsibilities will include solving technical challenges hands-on, shaping engineering best practices, coaching team members, and assisting cross-functional teams in delivering data products efficiently. You will be managing a small team of individual contributors responsible for developing and maintaining pipelines that facilitate reporting, analytics, and machine learning use cases. Your role will be crucial in driving engineering excellence, participating in sprint planning, architectural discussions, and collaborating with stakeholders as the data organization expands to meet increasing demand in various areas.

Key Responsibilities:

• Lead and nurture a team of data engineers focusing on ETL/ELT, data warehousing, and ML-enablement
• Take ownership of team deliverables in sprints, including planning, prioritization, QA, and stakeholder communication
• Establish and uphold robust engineering practices related to code reviews, testing, observability, and documentation
• Engage in cross-functional collaboration with Analytics, BI, Revenue Operations, and business stakeholders in Marketing and Sales
• Provide guidance on technical architecture decisions for pipelines on GCP (BigQuery, GCS, Composer)
• Model and transform data using dbt and SQL to support reporting, attribution, and optimization requirements
• Ensure data security, compliance, and scalability, particularly concerning first-party customer data
• Mentor junior engineers through activities such as code reviews, pairing, and technical roadmap discussions

Qualifications Required:

• 6+ years of experience in data engineering, with at least 2 years of people management or formal team leadership
• Proficiency in Python, Spark, Kafka, and orchestration tools like Airflow
• Extensive experience working on GCP, specifically BigQuery, GCS, and Composer
• Strong SQL skills and familiarity with DBT for modeling and documentation
• Sound understanding of data privacy and governance, including secure management and segmentation of first-party data
• Exposure to agile environments, encompassing sprint planning and ticket scoping
• Excellent communication skills and a demonstrated ability to collaborate effectively across global teams

Additional Company Details:

The company offers the following perks:

• Day off on the 3rd Friday of every month (one long weekend each month)
• Monthly Wellness Reimbursement Program to promote health and well-being
• Monthly Office Commutation Reimbursement Program
• Paid paternity and maternity leaves Role Overview:

You are being hired as a Data Engineering Lead to support and guide a growing team of data engineers. Your responsibilities will include solving technical challenges hands-on, shaping engineering best practices, coaching team members, and assisting cross-functional teams in delivering data products efficiently. You will be managing a small team of individual contributors responsible for developing and maintaining pipelines that facilitate reporting, analytics, and machine learning use cases. Your role will be crucial in driving engineering excellence, participating in sprint planning, architectural discussions, and collaborating with stakeholders as the data organization expands to meet increasing demand in various areas.

Key Responsibilities:

• Lead and nurture a team of data engineers focusing on ETL/ELT, data warehousing, and ML-enablement
• Take ownership of team deliverables in sprints, including planning, prioritization, QA, and stakeholder communication
• Establish and uphold robust engineering practices related to code reviews, testing, observability, and documentation
• Engage in cross-functional collaboration with Analytics, BI, Revenue Operations, and business stakeholders in Marketing and Sales
• Provide guidance on technical architecture decisions for pipelines on GCP (BigQuery, GCS, Composer)
• Model and transform data using dbt and SQL to support reporting, attribution, and optimization requirements
• Ensure data security, compliance, and scalability, particularly concerning first-party customer data
• Mentor junior engineers through activities such as code reviews, pairing, and technical roadmap discussions

Qualifications Required:

• 6+ years of experience in data engineering, with at least 2 years of people management or formal team leadership
• Proficiency in Python, Spark, Kafka, and orchestration tools like Airflow
• Extensive experience working on GCP, specifically BigQuery, GCS, and Composer
• Strong SQL skills and familiarity with DBT for modeling and documentation
• Sound understanding of data privacy and governance, including secure management and segmentation of first-party data
• Exposure to agile environments, encompassing sprint planning and ticket scoping
• Excellent communication skills and a demonstrated ability to collaborate effectively across global teams