GCP Architect

• 8+ years of experience in Data Engineering or L3 level of support in data Analytics General Description

• Experience with Data Lake, data warehouse ETL pipelines build and design.
• Hands-on with GCP data and analytics services - Cloud DataProc, Cloud Dataflow, Cloud Dataprep , Apache Beam/ composer, Cloud BigQuery,
• Data Pipeline Development: Design, develop, and maintain ETL/ELT pipelines to ensure seamless data flow from various sources to our data warehouse using DBT or GCP BigQuery.
• Data Modelling: Implement and manage data models in BigQuery to support business analytics and reporting needs.
• Version Control: Utilize GIT for version control to manage changes in data pipelines, schemas, and related code.
• Solid coding skills in languages such as SQL, Python, or Java
• 8+ years of experience as a Data Engineer or in a similar role

• Identify, create, maintain and support data model/data aggregation model base on business requirements and implement ETL for those models accordingly.
• Implement processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
• Implementing, establishing standards, and maintaining company data lake (UDP), regional platforms data streaming from Apache Kafka topics.
• Develop and maintains scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity.
• Collaborate with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility, and fostering data-driven decision making across the organization.
• Writes unit/integration tests, contributes to engineering wiki, and documents work.
• Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues.
• Works closely with a team of frontend and backend engineers, product managers, and analysts.
• Design data integrations and data quality framework.
• Design and evaluates open source and vendor tools for data lineage.
• Work closely with all business units and engineering teams to develop strategy for long term data platform architecture.
• Plan, create, and maintain data architectures while also keeping it aligned with business requirements.
• Work closely with business and application delivery team on new digital project/implementation to understand solution and implemented data structure so that all relevant data engineer work including reports and various data-related enhancement can be implemented accordingly as part of the project.
• Develop report/dashboard/dataset for business user base on request.
• Assist to support existing reports/dashboard/dataset and also maintain report/dashboard/dataset repository.

• Excellent communication and presentation skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Strong problem-solving and critical thinking skills.
• Exceptional project management and organizational abilities.
• Team collaboration and leadership skills.
• Demonstrate a general knowledge of market trends and competition.
• Be a strong team player.
• Client-focused approach with a commitment to delivering exceptional customer service.

• Google Professional Data Engineer
• Google Professional Data Architect