GCP Data Architect - 6+ years

Job Description

• Data Engineer Lead with 8-12 years of experience in designing, building, and delivering scalable data solutions on Google Cloud Platform (GCP).
• Proven expertise in leading cross-functional teams to execute complex data migration programs and develop end-to-end data pipelines using BigQuery, Apache Airflow, DBT, and Medallion Architecture
• Strong ability to translate business requirements into robust, scalable, and efficient data platforms that support analytics and enterprise decision-making.
• Demonstrated success in driving automation and modernization initiatives. Experienced in implementing modern data architecture patterns to improve data quality, processing efficiency, and operational performance.
• Possesses strong technical expertise in SQL, Python, PySpark, and GCP services, combined with leadership capabilities, proactive problem-solving, and a passion for building high-impact data engineering solutions.

Responsibilities:

• Platform Management: Oversee the architecture and management of GCP resources, particularly BigQuery, Databricks, and Kubernetes.
• Architecting Solutions: Design scalable and efficient data architectures tailored to specific business needs. Optimization of Workloads: Analyze and optimize data processing workloads to improve performance and reduce costs.
• Performance Measurement: Implement monitoring and performance metrics for data pipelines and applications. Cost Monitoring: Develop strategies for cost-effective resource usage, including budget tracking and optimization techniques.
• Collaboration: Work closely with data engineers, developers, and stakeholders to ensure seamless integration and functionality. Required Skills: GCP Expertise: In-depth knowledge of Google Cloud Platform services, particularly BigQuery, AlloyDB, and Kubernetes. Data Engineering: Experience with data modeling, ETL processes (Data flow, Data proc, Cloud functions, Cloud Run), and data warehousing (Big Query, GCS) and data ingestion (pub sub)
• Performance Tuning: Proven track record in optimizing data processing and query performance in BigQuery. Kubernetes Management: Proficient in deploying and managing containerized applications using Kubernetes.
• Cost Management: Familiarity with GCP billing and cost management tools to monitor and optimize cloud expenditure. Monitoring Tools: Experience with GCP monitoring and logging tools (e.g., Stackdriver, Cloud Monitoring).
• Required Years of Experience: 8-12 years experience