Senior Data Engineer (GCP)

We are seeking a Senior Data Engineer (Google Cloud Platform) . You will build reliable ETL and ELT pipelines, optimize SQL and orchestration in Apache Airflow and help teams turn raw data into trusted, ready-to-use datasets. You will partner with clients and delivery teams to improve quality, performance and operational stability across cloud data platforms.

Responsibilities

• Design and build scalable ETL and ELT pipelines using Python, SQL,Big Query and cloud-native services
• Develop and optimize complex SQL for transformation, validation, troubleshooting and performance
• Create and maintain data models and warehousing solutions that support quality, availability and scale
• Orchestrate workflows in Apache Airflow, including scheduling, monitoring and incident resolution
• Support pipeline delivery and platform operations across Google Cloud Platform and Amazon Web Services (AWS)
• Improve CI/CD, source control and automated deployment practices for data solution
• Investigate data, integration and infrastructure issues, driving root-cause analysis and fixes
• Collaborate with clients and cross-functional teams to clarify requirements, risks, dependencies and delivery plans

Requirements

• Hands-on experience building ETL and ELT pipelines and supporting data warehousing
• Advanced SQL skill set including optimization, data validation and complex transformation
• Python proficiency for pipeline development and software engineering practices
• Experience with distributed processing using PySpark or Apache Beam
• Practical cloud experience with Google Cloud Platform and or Amazon Web Services (AWS) for data workloads
• Workflow orchestration background with Apache Airflow or Google Cloud Composer
• Knowledge of data modeling data lifecycle management and data quality controls
• Clear communication with the ability to explain trade-offs, risks and solution options to stakeholders

Nice to have

• Infrastructure-as-code exposure using Terraform and or Kubernetes
• Streaming familiarity with Kafka and event-driven patterns
• Data integration tooling experience such as Fivetran