Data Engineer

• GA4 & Digital Data Integration: Design, build, and deploy robust ETL and data management processes specifically for ingesting, transforming, and loading high-volume digital analytics data from Google Analytics 4 (GA4) into BigQuery.

• BigQuery Data Architecture: Develop and optimize BigQuery datasets, tables, and views to support various analytical needs, ensuring efficient querying and data integrity.

• Data Pipeline Development: Design, build, and deploy ETL job workflows with reliable error/exception handling and rollback frameworks, primarily utilizing GCP services.

• GCP Resource Management: Monitoring and optimizing data processing and storage resources on GCP, with a focus on BigQuery performance and cost efficiency.

• Troubleshooting & Optimization: Troubleshooting and resolving data pipeline issues and performance bottlenecks, particularly those related to large-scale digital data processing.

• SQL Development: Write complex, customized SQL queries within BigQuery to manipulate data, generate automatic periodic reports, and support ad-hoc analytical requests.

• Python Development: Build applications and scripts using Python to automate data processes, integrate systems, and enhance data quality.

• Documentation & Best Practices: Document data engineering processes, best practices, and technical specifications, especially for GA4 data models and BigQuery schemas.

• Cross-functional Collaboration: Work collaboratively with Business Partner Teams and Business Stakeholders during project scoping and feasibility phases as a Subject Matter Expert (SME) for concept investigation/viability and technical impact; identify and communicate technical risks and mitigations.

• Agile Development: Conform to agile development practices Evolutionary design, refactoring, continuous integration/delivery, test-driven development.

• Production Support: Provide production support for data load jobs, ensuring the continuous flow of critical digital data.

• Application Maintenance: Maintain or upgrade existing data applications and pipelines.

• Technical Communication: Clearly communicate technical terms to non-technical people and help them understand why change might be required to achieve a specific goal or to complete a project.

• Attend key design meetings and provide support.

• Other ad hoc duties as required.

What youll need:

• Google Analytics 4 (GA4) Expertise: Proven experience in working with GA4 data, including understanding its data model, event-based tracking, and integration with BigQuery.

• BigQuery Mastery: 5+ years of hands-on experience with Google BigQuery, including advanced SQL techniques (CTEs, window functions, aggregate functions), schema design, and performance optimization.

• SQL Expertise: 5+ years of hands-on experience with advanced SQL techniques (CTEs, window functions, aggregate functions).

• Python Development: 5+ years of strong experience in Python programming (object-oriented/functional programming, Pandas, PySpark).

• Cloud Proficiency: 5+ years working with GCP tools/services (BigQuery, DataProc, DataFlow, Terraform, CloudRun, Cloud Functions, Pub/Sub, etc.) or equivalent cloud platforms like AWS or Azure.

• Data Modeling Expertise: Experience designing star schemas, analyzing data warehouses, and applying data warehouse methodologies, particularly in the context of digital analytics data.

• Source Control & CI/CD: Hands-on experience with GitHub or similar repositories, branching strategies, and CI/CD pipelines for data engineering workflows.

• Testing Skills: Proven ability to perform unit testing (SQL scripts, ETL modules), integration testing, and performance/load/stress testing.

• Education: Bachelor s degree in Computer Science, Engineering, Mathematics, or a related technical field preferred.

Bonus Skills:

• Knowledge of dbt (data build tool).

• Experience with other web analytics platforms or marketing data sources.

• Familiarity with Looker or other BI tools for data consumption.