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 Technical Requirements • 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. Soft Skills • 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. Certifications (Good to have) • Google Professional Data Engineer • Google Professional Data Architect Educational Qualifications • Bachelor's Degree in Computer Science, Computer Engineering or a closely related field.