Senior Architect, Data Classification and Governance

Pay Rate: $100 - $120/hour, depending on experience

Contract Length: Contract runs until March 31, 2027 (possibility of extension)

Location: Calgary (hybrid)

Raise is currently hiring a contract team member on behalf of our client. They’re expanding their team to meet growing needs, making this a unique prospect to work with an industry leader.

Description
Our client is seeking a Senior Architect, Data Classification and Governance to own the technology architecture standard for data governance across a heterogeneous estate in transition. This role advises developers, data architects, and data modellers on how to build classification, access control, retention, and quality directly into design and delivery decisions, working at the level of specific schema, model, and control choices rather than high-level principles. The successful candidate will define the target governance toolchain architecture, assess the current state of the estate, and prove each architecture standard with a working reference implementation rather than a document alone.

This is a hands‑on technical architecture role that spans structured, unstructured, and geospatial data, requiring both deep governance expertise and the credibility to sit in design reviews and give specific, implementable direction to development teams.

Responsibilities

Author the technology architecture standard for data governance, covering 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 data modellers on building governance into design and delivery at the level of specific schema, model, and control decisions; participate in design reviews and provide written governance assessments of in‑flight work

Define the classification approach for each data shape: structured data in custom application databases and the lakehouse, unstructured content in document and file estates, and geospatial data at the feature and attribute level

Define the target governance toolchain architecture across Microsoft Purview and Databricks Unity Catalog, including which is authoritative for classification, lineage, and glossary, how the two federate, and what neither covers natively

Assess the current estate to determine what is governed centrally, what is governed at source, and what is deferred; sequence governance against what the estate supports today versus what requires platform change

Advise the internal team that owns business data governance standards on technology feasibility, implementation effort, and downstream cost; identify gaps where those standards are silent, ambiguous, or unimplementable, and bring specific recommendations

Prove each architecture standard with a reference implementation or proof of concept so teams receive a working pattern rather than a document to interpret





Work with Data Architecture to embed governance into data contracts, schema ownership, and ingestion patterns so new data lands governed by default

Build internal staff capability through design coaching, pattern walkthroughs, and developer‑facing documentation; transfer each published standard to a named owner of record

Define the data quality technology architecture, including how rules are authored, where they execute, how failures are handled, and how quality is measured and reported, covering the full path from data submission or capture through ingestion to consumption

Establish where quality is enforced versus observed, including validation at point of submission/capture, contract enforcement at ingestion boundaries, and monitoring in the lakehouse; advise on the cost tradeoff between rejecting bad data early versus remediating downstream

Required Skills

Demonstrated experience translating data governance requirements into technology architecture that development teams actually built from; experience limited to framework or policy authorship will not meet this requirement

Demonstrated experience governing a heterogeneous estate in transition, including deciding what to govern centrally versus at source and sequencing realistically against legacy constraints

Unstructured data governance: sensitivity and retention labelling, scanning and auto‑classification, and DLP across document and file estates

A proven approach to classification in custom‑built applications, covering classification metadata in the application schema, capture at source, and propagation through change data capture into the Lakehouse

Ability to sit in a design review with developers and modellers and give specific, implementable direction on the design in front of them

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 rule authoring, execution, quarantine handling, and measurement; a scorecard without enforcement will not meet this requirement

Experience with data quality rule execution tooling and the tradeoffs between options, such as Databricks Lakehouse Monitoring, DLT or pipeline expectations, Microsoft Purview data quality, and open source frameworks

Recommended Skills

Geospatial data governance: classification and access control at the feature and attribute level, treatment of spatial file formats as governance objects, spatial metadata standards, and generalization or masking of sensitive locations as a privacy control

Hands‑on Microsoft Purview:



data map, scanning and classification rules, sensitivity labels, glossary, lineage, and integration with non‑Microsoft sources

Hands‑on Databricks Unity Catalog: catalogs, schemas, ownership, tags, grants, row and column level security, dynamic masking, audit logs, system tables

Experience with confidential or restricted data management

Change data capture pipelines, ideally Databricks Lakeflow Connect or equivalent

Azure, GitHub, and CI/CD for schema and policy as code

ROT analysis and duplicate detection across structured and unstructured content

Deliverables

Target governance toolchain architecture across Microsoft Purview and Databricks Unity Catalog, identifying the authoritative source for classification, lineage, and glossary, and where neither tool provides coverage

Data classification technology architecture standard addressing structured, unstructured, and geospatial data, including the approach for custom‑built applications

Access control technology architecture standard mapping classification to enforced controls at the application, database, Lakehouse, and geospatial layers

Metadata, lineage, and data quality technology architecture standards

Assessment of data quality tooling options across the target toolchain, with a recommendation on where rules are authored and where they execute

Education/Certification Requirements

University degree in a related discipline (data management, computer science, information management, geomatics, analytics) or equivalent demonstrated experience. Professional certification such as CDMP, CIMP, or DGSP is recommended. Demonstrated implementation experience is weighted above certification.

Looking for meaningful work? We can help
Raise is an established hiring firm with over 65 years of experience. We believe strongly in making the world a better place through work, which is why we’re a certified B Corporation and donate 10% of our profits to charity.

We strive to build teams that reflect the diversity of the communities we work in. We encourage all qualified applicants to apply, including people from traditionally underrepresented groups such as women, visible minorities, Indigenous peoples, people identifying as LGBTQ2SI, veterans, and people with visible/nonvisible disabilities.

We have a dedicated webpage for accommodations where you can learn more about what we offer, and request accommodation: https://raise.jobs/accommodations/

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📌 Senior Architect, Data Classification and Governance (Alberta)
🏢 Raise
📍 Alberta