Senior Data Engineer

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The Senior Data Engineer will design, build, and support data engineering solutions on Google Cloud Platform, with a focus on scalable data pipelines, database integration, and ETL processes that enable analytics, reporting, and downstream application consumption.

Responsibilities

• Design, develop, and maintain data pipelines using GCP services including BigQuery, Cloud Spanner, and Dataflow for batch and streaming data processing
• Build and support ETL/ELT workflows that extract, transform, and load data across Oracle, Spanner, SQL Server, PostgreSQL, and other relational databases
• Develop and optimize BigQuery datasets, tables, partitioning, and clustering strategies to support efficient querying and reporting
• Implement and tune Dataflow pipelines for data transformation, enrichment, and movement between source systems and target data stores
• Monitor and manage Compute Engine VMs, including CPU utilization, resource allocation, and performance tuning across GCP workloads
• Support and troubleshoot other core GCP technologies such as Cloud Storage, Cloud Composer, Pub/Sub, and IAM as part of end-to-end data workflows
• Apply data warehousing concepts including dimensional modeling, star/snowflake schemas, slowly changing dimensions, and data mart design
• Develop and support ETL workflows using tools such as Informatica, integrating with GCP and on-premise database systems
• Work extensively in Unix/Linux environments including shell scripting, file system navigation, permissions management, and log/file handling
• Schedule, monitor, and troubleshoot batch jobs using Control-M, ensuring timely and reliable execution of data pipelines
• Participate in Agile/JIRA-based development processes, including sprint planning, ticket tracking, status updates, and defect management
• Collaborate with senior engineers and architects on performance tuning, query optimization, and database design across multiple platforms
• Troubleshoot data pipeline failures, performance bottlenecks, and data quality issues across the stack
• Document technical designs, operational runbooks, and support procedures for the platforms being built
• Stay current with emerging AI/ML and GenAI tools and proactively apply them to improve productivity, automate repetitive tasks, and streamline development and data engineering workflows

Requirements

• 5+ years of experience in data engineering, software engineering, or database development
• 3+ years of hands-on experience with Google Cloud Platform (GCP) products, especially BigQuery, Cloud Spanner, and Dataflow
• Strong experience working with multiple database platforms, especially Oracle, Spanner, SQL, and PostgreSQL
• Working knowledge of Google ETL technologies and other core GCP services (Compute Engine/VMs, Cloud Storage, Cloud Composer, Pub/Sub)
• Experience with performance tuning, including CPU utilization analysis and resource optimization on GCP compute resources
• Solid understanding of data warehousing concepts (dimensional modeling, fact/dimension tables, ETL design patterns)
• Experience with ETL tools such as Informatica for data integration and transformation
• Strong Unix/Linux experience, including shell scripting and file system handling
• Experience with job scheduling tools such as Control-M
• Strong SQL development skills and ability to write/optimize complex queries

Benefits

• Medical, dental, and vision coverage
• Paid time off
• Retirement savings options
• Wellness programs
• Other resources, based on eligibility