Senior Data Engineer improving General Motors vehicle data pipelines, monitoring, and observability. Supporting reliable fleet software operations across Oshawa and Markham hybrid offices.
About the role
- GCP Data Platform Engineer maintaining and optimizing production data platforms for Innodata, a global data engineering and AI services company. Supporting Airflow pipelines, GCP infrastructure, reliability, and troubleshooting.
Responsibilities
- Support and maintain production GCP data platforms, pipelines, and workflows across batch and streaming workloads
- Troubleshoot and optimize Cloud Composer / Apache Airflow workflows, including DAG failures, dependencies, scheduling, retries, latency, and SLA issues
- Troubleshoot pipeline failures, data latency, performance degradation, configuration problems, and infrastructure issues
- Monitor platform health and improve reliability, scalability, performance, and operational efficiency
- Optimize existing pipelines and workloads to improve refresh times, throughput, query performance, and platform stability
- Support platform, infrastructure, configuration, and dependency upgrades while maintaining production stability and compliance
- Perform root-cause analysis and implement sustainable fixes for recurring production issues
- Support IAM, access controls, monitoring, alerting, logging, and operational governance
- Collaborate with client and cross-functional Data Engineering, BI/Analytics, Application Engineering, Infrastructure, and Platform teams
- Review existing architectures and recommend incremental improvements
- Create and maintain technical documentation, operational runbooks, troubleshooting guides, and platform support procedures
Requirements
- 3–7 years of experience in Data Engineering, Cloud Engineering, Platform Engineering, or a related role
- Strong hands-on experience building, supporting, or maintaining production workloads on Google Cloud Platform
- Strong experience with BigQuery and Cloud Spanner
- Hands-on experience with Dataflow, Pub/Sub, batch/streaming data pipelines, and Cloud Composer / Apache Airflow
- Strong Python and SQL skills
- Understanding of GCP IAM, service accounts, permissions, monitoring, logging, alerting, and production operations
- Experience troubleshooting complex production environments and performing root-cause analysis
- Understanding of data ingestion, transformation, orchestration, data quality, performance optimization, and reliability
- Ability to understand existing systems, codebases, pipelines, configurations, and client-specific tools and workflows
- Strong communication and collaboration skills
- Preferred: App Engine, Cloud Run, GKE, CI/CD and DevOps on GCP, Terraform, data observability, automated data-quality monitoring, Vertex AI, and enterprise analytics tooling
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