Key Responsibilities
1. Target State Design
- Design and implement a scalable, secure, and domain-driven Data Lakehouse architecture on GCP.
- Define enterprise-grade data architecture standards and reference frameworks.
2. Migration Leadership
- Lead end-to-end migration from legacy platforms (Exasol, Lua, Control-M) to GCP BigQuery and Dataform.
- Drive migration planning, execution, validation, and optimization.
3. Data Modeling
- Design conceptual, logical, and physical data models.
- Implement:
- Data Vault 2.0 (Silver Layer)
- Dimensional Modeling (Gold Layer)
4. Framework Development
- Build reusable, configuration-driven data pipeline frameworks.
- Establish best practices for scalable and accelerated development.
5. Governance & Security
- Implement enterprise data governance using:
- Dataplex
- Data Catalog
- Analytics Hub
- Enable data lineage, cataloging, automated data quality checks, and PII masking using DLP.
6. Orchestration & Automation
- Architect workflows using Cloud Composer (Airflow).
- Automate infrastructure provisioning through Terraform (IaC).
7. BI Modernization
- Reconfigure and validate:
- ~1,000 Tableau & Power BI dashboards
- ~250 semantic/data models
- Ensure successful migration to BigQuery curated layers.
8. Stakeholder Management
- Partner with Engineering Leads, Architects, and Business Teams.
- Translate business requirements into Technical Design Documents (TDDs).
- Drive architecture reviews and approvals.
9. Quality Assurance
- Conduct code reviews and enforce enterprise standards.
- Support UAT and automated validation using QuerySurge.
10. Team Leadership
- Mentor data engineering teams.
- Conduct technical enablement sessions and knowledge transfer workshops.
Required Skills & Experience
Data Engineering & Database Expertise
- Strong expertise in BigQuery architecture, optimization, and stored procedures.
- Advanced SQL programming skills.
- Experience modernizing legacy ETL (Lua-based) into modern ELT frameworks.
- Strong understanding of:
- Data Vault 2.0
- Dimensional Modeling
- Experience with Exasol or similar legacy data warehouses is highly preferred.
GCP & Modern Data Stack
- Hands-on experience with:
- BigQuery
- Dataform (Mandatory)
- Cloud Composer (Airflow)
- Dataflow
- GCS
- Deep expertise in:
- Dataplex
- Data Catalog
- Analytics Hub
Security & Governance
- Experience implementing:
- IAM Roles & Policies
- Cloud KMS
- DLP API
- Strong understanding of enterprise governance and compliance frameworks.
Architecture & DevOps
- Enterprise Data Architecture design experience.
- Cost estimation, sizing, and capacity planning on GCP.
- CI/CD implementation and Terraform-based infrastructure automation.
Soft Skills
- Strong stakeholder management and communication skills.
- Experience leading discovery and solution design workshops.
- Ability to lead distributed Agile/Scrum teams.
- Excellent technical documentation skills (TDD/TSD creation).
Must-Have Skills
- 10+ years of Data Engineering / Data Architecture experience.
- Expertise in GCP BigQuery and Dataform.
- Hands-on experience with Data Vault 2.0.
- Experience implementing Dataplex for governance and security.
- Strong Terraform expertise.
- Proven experience migrating legacy warehouses such as:
- Exasol
- Teradata
- Netezza
- Similar enterprise DW platforms
Good-to-Have Skills
- Lua scripting experience.
- Control-M orchestration experience.
- Tableau and Power BI semantic/data model migration.
- QuerySurge for automated data validation.
- GCP Professional Data Engineer or Professional Cloud Architect certification.
Ideal Candidate Profile
- 10–15+ years of Data Engineering/Data Architecture experience.
- Led large-scale cloud modernization programs.
- Strong expertise in GCP Lakehouse architecture, governance, and migration frameworks.
- Comfortable working with enterprise stakeholders and leading cross-functional migration initiatives.
Shubham Vishwakarma
Full Stack Developer - Averlon
About Quantiphi
About
Quantiphi is an award-winning AI-first digital engineering company driven by the desire to reimagine and realize transformational opportunities at the heart of the business. Since its inception in 2013, Quantiphi has solved the toughest and most complex business problems by combining deep industry experience, disciplined cloud, and data-engineering practices, and cutting-edge artificial intelligence research to achieve accelerated and quantifiable business results.
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