Data Engineer

Key Responsibilities

• Design, build, and maintain end-to-end GCP data pipelines for both batch and streaming workloads.
• Ensure high availability, reliability, and performance of data platforms in line with defined SLAs and SLOs.
• Develop and manage ETL/ELT workflows using Cloud Composer (Airflow), Dataflow (Apache Beam), and BigQuery.
• Manage and enhance data lakes and data warehouses using BigQuery and Cloud Storage.
• Implement real-time and streaming data solutions using Pub/Sub, Dataflow, or Kafka.
• Build and expose data APIs and microservices for data consumption using Cloud Run, Cloud Functions, or App Engine.
• Define and enforce data quality, governance, and lineage using Data Catalog and Cloud Data Quality tools.
• Collaborate closely with DevOps teams to implement CI/CD pipelines, infrastructure as code, and automated monitoring for data workflows.
• Participate in incident management, root cause analysis (RCA), and change control processes following ITIL best practices.
• Mentor junior engineers and ensure adherence to engineering standards and best practices.

Key Competencies

• Proven experience in managed service delivery environments with strict SLAs covering availability, latency, and resolution timelines.
• Strong understanding of Google Cloud Platform (GCP), IAM, and cloud cost management.
• Solid knowledge of incident, change, and problem management using ITSM tools such as ServiceNow or Jira.
• Ability to lead and manage on-call operations within a 16/5 support model, coordinating with global teams.
• Strong understanding of data security, governance, and compliance requirements.
• Excellent communication, stakeholder management, and client-facing skills.
• Comfortable working in a 16/5 model with teams across multiple time zones.