Senior Data Catalog Solution Engineer / Architect

Responsibilities are (but not limited to):

Architect & Implement Data Catalog Solutions

Lead the deployment and configuration of the enterprise data catalog (including data.world), ensuring alignment with organizational data governance frameworks.

Metadata & Lineage Management

Design metadata models, lineage tracking mechanisms, and business glossaries; implement automated metadata enrichment, sensitive data detection, and trust indicators.

Integration & Automation

Develop and maintain connectors to cloud and on-premises systems (e.g., Snowflake, Databricks, Tableau, Power BI, Salesforce), implement REST API and webhook integrations, and enable near real-time metadata synchronization.

Data Governance Enablement

Configure RBAC, data ownership models, approval workflows, and lifecycle tracking; establish certification processes for "golden" datasets.

Data Quality & Observability

Integrate with DQ/DO platforms (e.g., Monte Carlo, Anomalo, Soda), display quality metrics in the catalog, and build governance dashboards for monitoring health, freshness, and compliance.

Impact Analysis & Change Management

Utilize lineage graphs to perform upstream/downstream impact assessments, manage schema drift, and coordinate controlled metadata/schema releases.

Collaboration & Adoption

Provide technical guidance to analysts, data engineers, and business stewards; create best-practice documentation, onboarding guides, and training sessions to drive platform adoption.

Experience: 7+ years in Data Architecture, Data Engineering, or Metadata Management roles, with direct experience implementing enterprise data catalog platforms (data.world, Collibra, Alation, Informatica EDC, or similar).

Proven ability to design extensible metadata models, manage business glossaries, and implement automated enrichment processes (AI/ML-driven where applicable).

Hands-on experience with APIs, RESTful services, webhook/event-driven automation, and bulk metadata import/export processes.

Deep understanding of lineage capture across ingestion, transformation, and visualization layers; experience with cross-platform lineage visualization tools.

Strong knowledge of RBAC, sensitive data handling (PII/PHI/PCI), approval workflows, and compliance frameworks (GDPR, CCPA, HIPAA). Data Governance as a principle.

Familiarity with integrating catalog platforms with DQ/DO tools; ability to interpret and surface trust indicators and KPIs.

Technical Stack: Proficiency in SQL and one or more scripting languages (Python, Bash, etc.); experience with cloud data ecosystems (AWS, Azure, GCP).

Strong stakeholder engagement, requirement gathering, and cross-functional communication skills; ability to translate technical concepts into business value.

Direct implementation experience with data.world at enterprise scale.

Familiarity with semantic knowledge graphs, ontology/taxonomy modeling, and metadata-driven AI capabilities.

RDF / SPARQL.

Background in designing petabyte-scale metadata and governance solutions.

Exceptional logical reasoning and problem-solving skills

Hunger for learning new technologies with a "can do" mindset

Algorithmic and out of box thinking while working with requirements

Experience integrating with cloud infrastructure platforms, in particular Microsoft Azure

Understanding of Financial Mathematics