Data Analytics Engineer

SIMARN Solutions is seeking an experienced Data Analytics Engineer to design, develop, and optimize scalable data pipelines and analytics solutions on Google Cloud Platform. The role focuses on ETL/ELT pipelines, data modeling, BigQuery optimization, Python automation, data quality and governance, and delivering insights through Looker dashboards and reports.

Responsibilities:

• Design, develop, and maintain scalable ETL/ELT pipelines using Dataflow, Dataform, and BigQuery
• Develop data models, transformations, and analytics workflows
• Collaborate with data scientists, analysts, and business stakeholders to deliver insights through Looker dashboards and reports
• Ensure data quality, reliability, governance, and consistency across multiple data sources
• Optimize BigQuery queries, partitions, and clustering for performance and cost efficiency
• Develop Python scripts for automation, data processing, and API integrations
• Implement CI/CD practices for data pipeline deployments
• Monitor, troubleshoot, and improve data infrastructure performance and reliability
• Document data models, pipelines, dashboards, and technical processes
• Work closely with cross-functional teams to support data-driven business initiatives

Requirements:

• Visa: USC & GC Only
• 6–10 years of overall Data Analytics Engineering experience
• Strong hands-on experience with Google Cloud Platform (GCP)
• Strong experience with BigQuery
• Hands-on experience with Dataflow
• Experience developing dashboards and reporting solutions using Looker
• Strong programming experience with Python
• Experience with ETL/ELT pipeline development
• Strong understanding of data modeling and data transformation
• Experience with data quality, governance, monitoring, and troubleshooting
• Experience optimizing BigQuery queries, partitioning, and clustering
• Strong communication and collaboration skills
• Experience with Dataform
• Experience with CI/CD for data engineering projects
• Experience with API integrations and automation
• Experience with cloud-based data engineering environments
• Experience working with data scientists, analysts, and business stakeholders
• Experience with enterprise-scale data platforms and analytics solutions