Tech Stack
BigQueryCloudETLGoogle Cloud PlatformPythonSQL
About the role
- Assessments of existing data components, Performing POCs, Consulting to the stakeholders
- Proposing end to end solutions to an enterprise's data specific business problems, and taking care of data collection, extraction, integration, cleansing, enriching and data visualization
- Ability to design large data platforms to enable Data Engineers, Analysts & scientists
- Strong exposure to different Data architectures, data lake & data warehouse
- Define tools & technologies to develop automated data pipelines, write ETL processes, develop dashboard & report and create insights
- Continually reassess current state for alignment with architecture goals, best practices and business needs
- DB modeling, deciding best data storage, creating data flow diagrams, maintaining related documentation
- Taking care of performance, reliability, reusability, resilience, scalability, security, privacy & data governance while designing a data architecture
- Apply or recommend best practices in architecture, coding, API integration, CI/CD pipelines
- Coordinate with data scientists, analysts, and other stakeholders for data-related needs
- Help the Data Science & Analytics Practice grow by mentoring junior Practice members, leading initiatives, leading Data Practice Offerings
- Provide thought leadership by representing the Practice / Organization on internal / external platforms
Requirements
- Expertise in SQL, Python, ERD, GCP (All services, especially BigQuery, GCS, Cloud Function, Composer), DBT with Active/Heavy hands-on in the last 3~5 years
- Possess the knowledge of Modern Data Technology released in the last 2~3 years
- Design and optimize conceptual and logical database models
- Analyze system requirements, implementing data strategies, and ensuring the efficiency and security
- Improve system performance by conducting tests, troubleshooting, and integrating new elements
- In-depth understanding of database structure principles
- Expertise in implementing and maintaining data pipelines
- Deep knowledge of data mining and segmentation techniques
- 10+ years in data modeling with 3+ years in Big data (100TB+)
- Familiarity with data visualization tools
- Submission requires both Resume/Profile and code assessment result in SQL and Python (e.g. IKM CodeChek/TechChek)