Our team operates at the frontlines of our efforts to support Google and owns the campaign management functionalities that allow users to scale, automate and optimize their ad operations on Google Ads.

Join us in building new end-to-end automation solutions and scaling existing automation pipelines to help our customers automatically launch and iterate their Google advertising.

The team has recently started working with exciting new campaign types within Google Ads and we’re looking to scale up our team to expand our Google Ads offering.

Requirements:

• 5+ years of hands-on experience in data engineering
• Strong experience with Python and SQL
• 3+ years of experience with cloud vendors (AWS/Azure/GCP), DWH services (Redshift, Databricks etc.), cloud storages (Azure Storage, S3)
• Strong experience with ETL/ELT/orchestration tools (Airflow, ADF, Glue, Nifi)
• Drive the design and implementation of data warehouse and data lakes
• Proficient in code versioning (git) and building CI/CD for data projects
• Experience with requirement gathering and documentation.

Will be a plus:

• Experience with NoSQL
• Experience with stream processing (e.g., Apache Kafka, Apache Flink, Spark Structured Streaming)

Responsibilities:

• Collaborate with business stakeholders and technical teams to understand and analyze data requirements
• Lead the design and implementation of data models and database structures that meet business needs
• Profile, refactor, and tune performance in the database
• Design and implement complex ETL processes to extract, transform, and load data from various source systems into the data warehouse
• Ensure data integrity, consistency, and accuracy through robust data quality assurance measures
• Review and support team members, providing guidance and mentorship
• Supervise and contribute to the data-driven strategy for the project, aligning it with business objectives