Senior Data Consultant

Solvd

20h

About The Position

Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes. Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively. We are seeking a Senior Consultant / Lead to lead the end-to-end design of a secure, governed, enterprise-scale Data Lakehouse platform for a FinTech organization. This role will be responsible for defining and implementing a future-proof security, governance, and interoperability.

Requirements

Databricks Lakehouse (advanced hands-on)
Unity Catalog governance model
Azure Fabric (including Power BI integration)
Azure ecosystem (Key Vault, Private Endpoints, Event Hubs, networking)
Tokenization (vaulted and vaultless)
Encryption (FPE, deterministic tokens)
Masking (dynamic masking, row-level security)
PII governance in banking/FinTech environments
Experience with Protegrity or Thales CipherTrust
ETL/ELT pipeline design
Structured Streaming / CDC
Delta Lake architecture
Bronze/Silver/Gold patterns
CI/CD for data platforms
PCI-DSS implications on analytics
Key management best practices
Audit logging frameworks
Role-based and attribute-based access control
Enterprise data catalog design

Responsibilities

Design end-to-end PII data protection strategy (tokenization, encryption, masking).
Implementing secure ingestion patterns (event-driven + batch).
Define where tokenization occurs (inline vs ingestion vs vault-based).
Ensure PCI/PII data does not unnecessarily enter analytics layers.
Integrate Protegrity or Thales into data pipelines with proper policy enforcement.
Define encryption key management strategy (HSM/KMS integration, key rotation, separation of duties).
Design Unity Catalog structure (catalogs, schemas, privilege hierarchy).
Define RBAC/ABAC strategy aligned with enterprise security model.
Implement row-level and column-level security policies.
Ensure audit logging and monitoring is properly configured.
Prevent role sprawl and access duplication.
Define secure workspace isolation patterns (PCI vs non-PCI).
Design governance model that avoids duplication between: Unity Catalog, Azure Fabric security model, Power BI semantic layer security.
Ensure role propagation and access alignment across platforms.
Define how security roles translate from: Databricks → Fabric → Power BI.
Avoid redundant catalog definitions or policy conflicts.
Design data contract model that supports centralized metadata management.
Align data catalog strategy (Purview / Unity Catalog / Fabric metadata).
Lead migration of legacy ETL pipelines into Lakehouse architecture.
Define phased modernization strategy (Bronze/Silver/Gold).
Implement event-driven real-time ingestion patterns where required.
Ensure secure data flow with encryption in transit and at rest.
Design data quality validation framework.
Establish CI/CD practices for pipelines and governance rules.