Data Engineer III

Design, develop, and maintain scalable ETL/ELT data pipelines supporting enterprise data products and analytics.

Build and optimize data solutions using Google BigQuery, GCS, Cloud Composer/Airflow, dbt, Python, and SQL .

Develop robust data ingestion and transformation pipelines from databases, SaaS applications, APIs, files, and other enterprise data sources.

Implement and maintain API integrations and data ingestion frameworks for cloud and enterprise applications.

Develop reusable dbt models, transformation frameworks, and data quality processes .

Build and manage workflow orchestration using Apache Airflow / Google Cloud Composer .

Work with CDC and data ingestion technologies such as Informatica CDC, Airflow, Composer, dbt, or similar platforms .

Design and implement modern data lakehouse architectures using BigQuery and related cloud technologies.

Optimize data pipelines and BigQuery workloads for performance, scalability, reliability, and cost efficiency .

Implement engineering best practices including CI/CD, version control, automated testing, deployment automation, and DevOps practices .

Contribute to data observability and monitoring frameworks , including pipeline health, data quality, SLA monitoring, and operational metrics.

Partner with data architects, analysts, data scientists, product teams, and business stakeholders to deliver high-quality data solutions.

Contribute to data governance, metadata management, lineage, and data discovery capabilities.

Explore and implement AI/ML and GenAI capabilities to improve data engineering workflows, automation, data discovery, and developer productivity.

Troubleshoot complex data pipeline and platform issues and drive root-cause analysis and long-term improvements.

Help establish engineering standards, reusable frameworks, and best practices across the Global Data organization.

• Champion self-service data capabilities that improve the experience of data consumers and engineering teams.