Cloud Data Engineer responsible for modern Data & AI solutions on Microsoft Azure. Collaborating with clients and teams to develop production - ready data platforms and support analytics.
About the role
- Data Engineer focusing on building scalable data solutions with GCP and BigQuery for Fortune 500 companies. Join our team to architect data pipelines and support analytics initiatives.
Responsibilities
- Design, build, and maintain scalable and reliable batch and real-time ETL/ELT data pipelines using GCP services like Dataflow, Cloud Functions, Pub/Sub, and Cloud Composer.
- Develop and manage our central data warehouse in Google BigQuery. Implement data models, schemas, and table structures optimized for performance and scalability.
- Write clean, efficient, and robust code (primarily in SQL and Python) to transform raw data into curated, analysis-ready datasets.
- Monitor, troubleshoot, and optimize our data infrastructure for performance, reliability, and cost-effectiveness. Implement BigQuery best practices, including partitioning, clustering, and materialized views.
- Build and maintain curated data models that serve as the "source of truth" for business intelligence and reporting, ensuring data is ready for consumption by BI tools like Looker.
- Implement automated data quality checks, validation rules, and monitoring to ensure the accuracy and integrity of our data pipelines and warehouse.
- Work closely with software engineers, data analysts, and data scientists to understand their data requirements and provide the necessary infrastructure and data products.
Requirements
- 3-5+ years of hands-on experience in a Data Engineering, Software Engineering, or a similar role.
- Strong proficiency in a programming language such as Python or Java for data processing and automation.
- Mastery of SQL for complex data manipulation, DDL/DML operations, and query optimization.
- Proven expertise in using BigQuery as a data warehouse, including data modeling, performance tuning, and cost management.
- Hands-on experience building data pipelines using the GCP ecosystem (e.g., Dataflow, Pub/Sub, Cloud Storage, Cloud Composer/Airflow).
- Deep understanding of ETL/ELT principles and data warehousing architecture (e.g., Star Schema, Data Lakes).
- Strong problem-solving and troubleshooting skills with a focus on building scalable, maintainable, and automated systems.
Benefits
- Comprehensive Benefits: We cover 100% of health, dental, and vision insurance premiums for you and your dependents which means no out-of-pocket costs. Eligibility starts from day one itself.
- Access extensive learning and development resources to keep leveling up your skills.
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