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Sr Architect - Data Classification & Governance

Procom
Calgary, AB

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Détails du poste

Contrat
Il y a 18 heures

Compétences

CI/CD
Databricks
Modélisation de données
Azure
Coaching
Gouvernance des données
Baccalauréat
Contrôle de la qualité
Rédaction technique
GitHub
Consultation auprès de la clientèle
Métadonnée

Description complète du poste

Senior Architect, Data Classification and Governance:
On behalf of our client, Procom is searching for a Senior Architect, Data Classification and Governance for a contract role running September 14, 2026 to March 31, 2027, with possible extension. This position is full onsite at our client's downtown location.

Senior Architect, Data Classification and Governance - Job Description:
We are seeking a Senior/Expert-level architect to own the technology architecture standard for data governance across a heterogeneous data estate in transition. This person advises developers, data architects, and data modelers on building classification, access control, retention, and quality directly into design and delivery, and defines the target governance toolchain across Microsoft Purview and Databricks Unity Catalog.

Responsibilities:

Author the technology architecture standard for data governance: classification, metadata and tagging, access control, retention, quality instrumentation, lineage, and reference data change control across structured, unstructured, and geospatial data
Advise developers, data architects, and modelers on embedding governance at the schema, model, and control-decision level. Sit in design reviews and issue written governance assessments
Define classification approach per data shape: structured (custom apps, lakehouse), unstructured (documents/files), geospatial (feature/attribute level)
Define target governance toolchain across Microsoft Purview and Databricks Unity Catalog, including which system is authoritative for classification, lineage, and glossary
Assess the current estate to determine what's governed centrally vs. at source vs. deferred, and sequence governance against what the estate can support today
Advise client's business data governance standards owners on technical feasibility, effort, and cost, and bring specific recommendations where those standards are silent or unimplementable
Prove each standard with a reference implementation or POC
Embed governance into data contracts, schema ownership, and ingestion patterns with Data Architecture
Build client staff capability through coaching and documentation, and transfer each standard to a named client owner
Define the data quality technology architecture: rule authoring, execution, failure handling, and measurement/reporting end to end
Establish where quality is enforced vs. observed, and advise on the tradeoff between rejecting bad data early vs. remediating downstream

Mandatory Skills:

Demonstrated experience translating data governance requirements into architecture that dev teams actually built from (framework/policy authorship alone doesn't qualify)
Experience governing a heterogeneous estate in transition, including central-vs-source decisions and realistic sequencing against legacy constraints
Unstructured data governance: sensitivity/retention labelling, scanning/auto-classification, DLP
Proven approach to classification in custom-built applications, including CDC propagation into the Lakehouse
Ability to give specific, implementable direction in live design reviews
Strong technical writing, standards must be usable by a developer without the author present
Demonstrated design of a data quality framework that reached production, including enforcement (a scorecard alone won't qualify)
Experience with DQ rule execution tooling tradeoffs (Databricks Lakehouse Monitoring, DLT/pipeline expectations, Microsoft Purview DQ, open source)

Nice-to-Have Skills:

Geospatial data governance (classification, masking, spatial metadata standards)
Hands-on Microsoft Purview (data map, scanning, sensitivity labels, glossary, lineage)
Hands-on Databricks Unity Catalog (catalogs, schemas, grants, row/column security, dynamic masking, audit logs)
Confidential/restricted data management experience
CDC pipelines, ideally Databricks Lakeflow Connect
Azure, GitHub, CI/CD for schema and policy as code
ROT analysis and duplicate detection

Education/Certification: University degree in a related discipline or equivalent experience. CDMP, CIMP, or DGSP recommended but implementation experience is weighted higher.

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Sr Architect - Data Classification & Governance

PLEXOS Modeling Consultant

Lead Product Security

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