Lead Data Engineer

Responsibilities

• Develop and maintain robust data pipelines to manage large, complex datasets, ensuring they meet functional and non-functional business requirements.
• Drive process improvements by automating manual tasks, optimizing data delivery, and re-architecting transformations for enhanced scalability.
• Leverage Google Cloud Platform (GCP) services for efficient data extraction, transformation, and loading (ETL) from diverse data sources.
• Collaborate with Product, Data, and Design teams to address data-related technical challenges and fulfill data requirements.

Requirements

• Bachelor's degree and a minimum of 1.5 years of experience working effectively in globally distributed teams.
• Proficiency in Python and data handling frameworks such as Spark and Beam.
• Demonstrated experience with cloud storage and computing services within GCP (e.g., GCS, BigQuery, Composer) for data pipeline development.
• Experience in writing and orchestrating data pipelines using Airflow.
• Familiarity with handling data from third-party providers like Google Analytics and Google Ads is highly advantageous.
• Proven ability to manipulate, process, and extract valuable insights from large, disparate datasets.
• Solid understanding of software engineering practices in data engineering, including release management and testing, utilizing tools like dbt and Great Expectations.
• Basic knowledge of dbt is considered a plus.
• Understanding of data privacy and security principles.
• Excellent verbal and written communication skills.

Perks:

• Enjoy monthly long weekends with every third Friday off.
• Receive a wellness reimbursement to support your health and work-life balance.
• Benefit from paid parental leave.
• Experience a remote-first work environment offering flexibility and trust.
• Join a world-class data and marketing team within a globally recognized brand.