Data Engineer III – Global Data Team

About the role

We are seeking an experienced Data Engineer to join our Global Data team. The role focuses on designing, building, and optimizing cloud‑based data platforms and lakehouse architectures that power enterprise analytics and data products. You will work with a modern GCP stack to deliver reliable, scalable, and self‑service data solutions.

Key responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines supporting enterprise data products and analytics.
• Build and optimize solutions using BigQuery, Cloud Storage, Cloud Composer/Airflow, dbt, Python, and SQL.
• Create robust ingestion pipelines from databases, SaaS applications, APIs, and files.
• Implement API integrations and data ingestion frameworks for cloud and enterprise applications.
• Develop reusable dbt models, transformation frameworks, and data‑quality processes.
• Manage workflow orchestration with Apache Airflow / Google Cloud Composer.
• Work with CDC technologies such as Informatica CDC and related platforms.
• Design modern lakehouse architectures and optimize BigQuery workloads for performance, cost, and reliability.
• Apply engineering best practices including CI/CD, version control, automated testing, and DevOps.
• Contribute to data observability, monitoring, governance, metadata management, and lineage.
• Collaborate with data architects, analysts, data scientists, product teams, and business stakeholders.
• Explore AI/ML and GenAI capabilities to improve data‑engineering workflows.

Required profile

• 6–10 years of hands‑on data‑engineering experience.
• Strong problem‑solving skills and a passion for building reusable frameworks.
• Experience delivering self‑service data platforms in a cloud environment.
• Ability to work collaboratively with cross‑functional teams.

Required skills

• Google Cloud Platform (GCP) services: BigQuery, Cloud Storage, Dataflow, Data Fusion, Data Streams.
• Workflow orchestration: Cloud Composer, Apache Airflow.
• Data transformation: dbt, Python, SQL.
• CDC tools: Informatica CDC (or similar).
• CI/CD pipelines, version control (Git), automated testing, DevOps practices.
• Data observability and monitoring frameworks.
• Data governance, metadata management, lineage.
• Familiarity with AI/ML or GenAI concepts for data engineering.