GCP Architect

Data Engineer Position

Experience with Data Lake, data warehouse ETL pipelines build and design. Hands-on with GCP data and analytics services - Cloud Data Proc, Cloud Dataflow, Cloud Dataprep, Apache Beam/composer, Cloud Big Query.

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 Big Query.

Data Modelling:
Implement and manage data models in Big Query 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.

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 (Good to have)

Bachelor's Degree in Computer Science, Computer Engineering or a closely related field.