true
Senior
<div class="_descriptionText_oj0x8_198"><h2>About the project</h2><p>Join Neurons Lab as a <strong>Senior GCP Data Architect</strong> working on <strong>banking data lake and reporting systems</strong> for large financial institutions. This is an end-to-end role where you'll start with presales and architecture - gathering requirements, designing solutions, establishing governance frameworks - then progress to implementing your designs through to MVP delivery.</p><p><strong>Our Focus</strong>: Banking and Financial Services clients with stringent regulatory requirements (Basel III, MAS TRM, PCI-DSS, GDPR). You'll architect data lake solutions for critical use cases like AML reporting, KYC data management, and regulatory compliance - ensuring robust data governance, metadata management, and data quality frameworks.</p><p><strong>Your Impact</strong>: Design end-to-end data architectures combining <strong>GCP data services</strong> (BigQuery, Dataflow, Data Catalog, Dataplex) with <strong>on-premise systems</strong> (ex. Oracle). Establish data governance frameworks with cataloging, lineage, and quality controls. Then build your designs - implementing data pipelines, governance tooling, and delivering working MVPs for mission-critical banking systems.</p><p><strong>Duration:</strong> Part-time long-term engagement with project-based allocations</p><p><strong>Reporting:</strong> Direct report to Head of Cloud</p><h2>Objective</h2><p>Design and deliver data lake solutions for banking clients on Google Cloud Platform:</p><ul><li><p><strong>Architecture Excellence</strong>: Design data lake architectures, create technical specifications, lead requirements gathering and solution workshops</p></li><li><p><strong>MVP Implementation</strong>: Build your designs - implement data pipelines, deploy governance frameworks, deliver working MVPs with data quality</p></li><li><p><strong>Data Governance</strong>: Establish and implement comprehensive governance frameworks including metadata management, data cataloging, data lineage, and data quality standards</p></li><li><p><strong>Client Success</strong>: Own the full lifecycle from requirements to MVP delivery, ensuring secure, compliant, scalable solutions aligned with banking regulations and GCP best practices</p></li><li><p><strong>Knowledge Transfer</strong>: Create reusable architectural patterns, data governance blueprints, implementation code, and comprehensive documentation</p></li></ul><h2>KPI</h2><ul><li><p>Design data architecture comprehensive documentation and governance framework</p></li><li><p>Deliver MVP from architecture to working implementation</p></li><li><p>Establish data governance implementations including metadata catalogs, lineage tracking, and quality monitoring</p></li><li><p>Achieve 80%+ client acceptance rate on proposed data architectures and technical specifications</p></li><li><p>Implement data pipelines with data quality and comprehensive monitoring</p></li><li><p>Create reusable architectural patterns and IaC modules for banking data lakes and regulatory reporting systems</p></li><li><p>Document solutions aligned with banking regulations (Basel III, MAS TRM, AML/KYC requirements)</p></li><li><p>Deliver cost models and ROI calculations for data lake implementations</p></li></ul><h2>Areas of Responsibility</h2><p><strong>Phase 1: Data Architecture & Presales</strong></p><ul><li><p>Elicit and document requirements for data lake, reporting systems, and analytics platforms</p></li><li><p>Design end-to-end data architectures: ingestion patterns, storage strategies, processing pipelines, consumption layers</p></li><li><p>Create architecture diagrams, data models (dimensional, data vault), technical specifications, and implementation roadmaps</p></li><li><p><strong>Data Governance Design</strong>: Design metadata management frameworks, data cataloging strategies, data lineage implementations, data quality monitoring</p></li><li><p>Evaluate technology options and recommend optimal GCP and On Premises data services for specific banking use cases</p></li><li><p>Calculate ROI, TCO, and cost-benefit analysis for data lake implementations</p></li><li><p><strong>Banking Domain</strong>: Design solutions for AML reporting, KYC data management, regulatory compliance, risk reporting</p></li><li><p><strong>Hybrid Cloud Architecture</strong>: Design integration patterns between GCP and on-premise platforms (ex. Oracle, SQL Server)</p></li><li><p>Security & compliance architecture: IAM, VPC Service Controls, encryption, data residency, audit logging</p></li><li><p>Participate in presales activities: technical presentations, client workshops, demos, proposal support</p></li><li><p>Create detailed implementation roadmaps and technical specifications for development teams</p></li></ul><p><strong>Phase 2: MVP Implementation & Delivery</strong></p><ul><li><p>Build production data pipelines based on approved architectures</p></li><li><p>Implement data warehouses: schema creation, partitioning, clustering, optimization, security setup</p></li><li><p>Deploy data governance frameworks: Data Catalog configuration, metadata tagging, lineage tracking, quality monitoring</p></li><li><p>Develop data ingestion patterns from on-premise systems</p></li><li><p>Write production-grade data transformation, validation, and business logic implementation</p></li><li><p>Develop Python applications for data processing automation, quality checks, and orchestration</p></li><li><p>Build data quality frameworks with validation rules, anomaly detection, and alerting</p></li><li><p>Create sample dashboards and reports for business stakeholders</p></li><li><p>Implement CI/CD pipelines for data pipeline deployment using Terraform</p></li><li><p>Deploy monitoring, logging, and alerting for data pipelines and workloads</p></li><li><p>Performance tuning and cost optimization for production data workloads</p></li><li><p>Document implementation details, operational runbooks, and knowledge transfer materials</p></li></ul><h2><strong>Skills & Knowledge</strong></h2><p><strong>Certifications & Core Platform:</strong></p><ul><li><p><strong>GCP Professional Cloud Architect</strong> (strong plus, not mandatory) - demonstrates GCP expertise</p></li><li><p><strong>GCP Professional Data Engineer</strong> (alternative certification)</p></li><li><p>Core GCP data services: BigQuery, Dataflow, Pub/Sub, Data Catalog, Dataplex, Dataform, Composer, Cloud Storage, Data Fusion</p></li></ul><p><strong>Must-Have Technical Skills:</strong></p><ul><li><p><strong>Data Architecture</strong> (expert level) - data lakes, lakehouses, data warehouses, modern data architectures</p></li><li><p><strong>Data Governance</strong> (expert level) - metadata management, data cataloging, data lineage, data quality frameworks, hands-on implementation</p></li><li><p><strong>SQL</strong> (advanced-expert level) - production-grade queries, complex transformations, window functions, CTEs, query optimization, performance tuning</p></li><li><p><strong>Data Modeling</strong> (expert level) - dimensional modeling, data vault, entity-relationship, schema design patterns for banking systems</p></li><li><p><strong>ETL/ELT Implementation</strong> (advanced level) - production data pipelines using Dataflow (Apache Beam), Dataform, Composer, orchestration</p></li><li><p><strong>Python</strong> (advanced level) - production data applications, pandas/numpy for data processing, automation, scripting, testing</p></li><li><p><strong>Data Quality</strong> (advanced level) - validation frameworks, monitoring strategies, anomaly detection, automated testing</p></li></ul><p><strong>BFSI Domain Knowledge (MANDATORY):</strong></p><ul><li><p><strong>Banking data domains</strong>: AML (Anti-Money Laundering), KYC (Know Your Customer), regulatory reporting, risk management</p></li><li><p><strong>Financial regulations</strong>: Basel III, MAS TRM (Monetary Authority of Singapore Technology Risk Management), PCI-DSS, GDPR</p></li><li><p>Understanding of banking data flows, reporting requirements, and compliance frameworks</p></li><li><p>Experience with banking data models and financial services data architecture</p></li></ul><p><strong>Strong Plus:</strong></p><ul><li><p>On-premise data platforms: Oracle, SQL Server, Teradata</p></li><li><p>Data quality tools: Great Expectations, Soda, dbt tests, custom validation frameworks</p></li><li><p>Visualization tools: Looker, Looker Studio, Tableau, Power BI</p></li><li><p>Infrastructure as Code: Terraform for GCP data services</p></li><li><p>Streaming data processing: Pub/Sub, Dataflow streaming, Kafka integration</p></li><li><p>Vector databases and search: Vertex AI Vector Search, Elasticsearch (for GenAI use cases)</p></li></ul><p><strong>Communication:</strong></p><ul><li><p><strong>Advanced English</strong> (written and verbal)</p></li><li><p>Client-facing presentations, workshops, and requirement gathering sessions</p></li><li><p>Technical documentation and architecture artifacts (diagrams, specifications, data models)</p></li><li><p>Stakeholder management and cross-functional collaboration</p></li></ul><h2>Experience</h2><ul><li><p><strong>7+ years</strong> in data architecture, data engineering, or solution architecture roles</p></li><li><p><strong>4+ years</strong> hands-on with <strong>GCP data services</strong> (BigQuery, Dataflow, Data Catalog, Dataplex) - production implementations</p></li><li><p><strong>3+ years</strong> in <strong>data governance</strong> (MANDATORY) - metadata management, data lineage, data quality frameworks, data cataloging</p></li><li><p><strong>3+ years</strong> in <strong>BFSI/Banking domain</strong> (MANDATORY) - AML, KYC, regulatory reporting, compliance requirements</p></li><li><p><strong>5+ years</strong> with <strong>SQL</strong> and relational databases - complex query writing, optimization, performance tuning</p></li><li><p><strong>3+ years</strong> in <strong>data modeling</strong> - dimensional modeling, data vault, or other data warehouse methodologies</p></li><li><p><strong>2+ years</strong> in <strong>presales/architecture</strong> roles - requirements gathering, solution design, client presentations</p></li><li><p><strong>Experience with on-premise data platforms</strong> (MANDATORY) - Ex. Teradata, Oracle, SQL Server integration with cloud</p></li></ul></div>