Project Role Description:

Design, develop, and maintain data solutions for data generation, collection, and processing.
Create data pipelines and ensure data quality.
Implement ETL (extract, transform, and load) processes to migrate and deploy data across systems.
Collaborate with cross-functional teams to understand data requirements and deliver effective solutions.
Troubleshoot issues in data flow and processing stages.
Enhance data infrastructure to ensure data accessibility and reliability for decision-making.

Roles & Responsibilities:

Deliver data integration and data warehousing solutions.
Develop and optimize SQL queries, particularly in Google BigQuery.
Work with cloud-native services such as bucket storage, Google BigQuery, Cloud Functions, Pub/Sub, Composer, and Kubernetes.
Automate CI/CD pipelines using tools like Azure DevOps (AZDO), Control-M, GitHub, JIRA, and Confluence.
Perform performance tuning of BigQuery SQL scripts.
Use Python for scripting and data manipulation, leveraging libraries such as Pandas and NumPy.
Work in an agile environment and adapt quickly to new technologies.
Collaborate effectively with various teams and work independently when required.
Participate in shift B work schedule and contribute as an individual contributor.

Professional & Technical Skills:

Must have skills: Google BigQuery, SQL, Python (including Pandas, NumPy), Shell Scripting
Good to have skills: Google Cloud Data Services, Microsoft SQL Server, GCP Certification
Experience with data processing, Pub/Sub, Dataflow, Kafka streaming, Looker
Strong knowledge of cloud-native data platform services
Experience in CI/CD pipeline automation and performance tuning

Professional Attributes:

Educational Qualification:

Additional Information:

Data Engineer