Pipeline run
fc3d1b12-2b6c-4d63-bcec-f2574b117d97
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionvocab breakdown (legacy)
Signals
Post-classification
Captured for admin review
• Ability to co-design the information architecture for different MDM solutions • Guide on the development and delivery of a series of major and minor releases through the year as specified by the roa…
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Data Governance Engineer
domain · Data Engineering & Analytics CASE DOMAINslug: data-governance-engineer · id: 146 · source: db
Domain=Data Engineering & Analytics; The JD centers on master data management, data governance, information architecture, match-and-merge rules, and MDM solution oversight, which best aligns with Data Governance Engineer.
Matched skills
Matched dimensions
Matched KRAs
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
• Join a business empowering people with data & technology|Be part of and exciting and evolving Data & Analytics journey About Our Client For Unilever to remain ruthless in the future, the business needs to continue the path to become data intelligent. The Data & Insights team will persevere to make Unilever Data Intelligent, powering key resolutions with data, insights, advanced analytics, and AI. Our goal is to enable democratization of data, information and insights as a completely agile organization that builds fantastic careers for our people and is accountable for delivering great work that maximizes impact and delivers growth. This Data & Analytics function endeavours to create clear accountabilities for all aspects of Data Strategy, Data Management, Information Management, Analytics, and Insights. We would be accountable for impact of solutions, maintaining market relevance and minimising unnecessary overlaps in analytics products, ensuring simplicity and that our solutions better meet the needs of our users. We would partner with the Digital and Data Legal Counsel to ensure that our Data Defence (Privacy, Governance, Quality, etc) is well structured and sufficiently robust to use data and AI correctly throughout the enterprise. We would democratize information across the business, while supporting the culture shift required for data carrying resolution making. Further, this team would drive capacity unlock from manual and duplicative reporting capabilities, while also refocusing a portion of the unlock on embedding predictive and prescriptive analytics capabilities into our highest potential opportunities. We have four key operating postulates: • One team • Connected to the business • Deploying with pace and discipline • Designing for experience Job Description Key Responsibilities: • Ability to co-design the information architecture for different MDM solutions • Guide on the development and delivery of a series of major and minor releases through the year as specified by the roadmap • Ensure the performance, quality and fit for market needs of the MDM output • Work collaboratively with the wider team to ensure on-time and in-full delivery • Configuring the MDM match and merge rules • Manage the wider development team • Assist in upskilling team members on Informatica solution • Work with the DevOps team on issues relating to the live service • Monitor third-party delivery quality to ensure it meets with Unilever standards. • Review and enhance the technical standards of the implementation • Ensure information security and personal information policies are abided and always front of mind for the wider development team • Ability to shape master data management strategy • Data governance The Successful Applicant Experience and qualifications required: Essential: • Strong working knowledge of Informatica MDM tool • Proven success in roles guiding design and configuration of MDM implementations • Demonstrated ability to work with upstream and downstream elements impacting and being impacted by the application • Ability to explain technical aspects to business users and helping them refine requirements as needed • Experience performing root cause analysis and resolution of issues • Ability to work both unaccompanied and collaboratively to resolve issues • Prior experience working with Informatica cloud offerings, including Informatica C360 • Experience of Agile/DevOps development lifecycle from conception to delivery. • Technical knowledge on Cloud based data and analytics tools and technologies, specifically Azure, Data Lake Store, Azure Data Factory, Azure Databricks • Experience of working with and managing supplier teams/resources. • Excellent verbal, written and interpersonal communication skills. • Possesses good analytical thinking to develop solutions and propose action plans • Ability to learn new tools, technologies, and process quickly • Self-motivated problem solver; able to thrive in a dynamic and result-carrying environment • Thorough understanding of applicable standards and procedures including technical, quality, safety, and financial matters across all areas of delivery Desirable: Prior development/design experience on IDQ Informatica module Professional certification (Agile methodologies, PMI, ITIL, etc.) Domain expertise in Analytics and Data Lake Platform & Technologies Experience of working within consumer goods or retail industry. Key Interfaces: Internal • Data SMEs, Business Data Lake Factory, Unilever data lake, Cloud platform (landscape) team, Technical Design Authority, other UniOps teams. • Data & Analytics Management team. External Third-party resources working within Data Lake delivery. Standards of Management • Passion for High Performance (Inspires the energy needed to win and grow) • Keen to continuously learn • Agility (constantly curious & daring) What's On Offer What do we offer: From our foundation, Unilever has been a purpose-driven company. Today, our purpose is to make sustainable living commonplace. We are working to create a brighter future every day with brands and services that help people feel good, look good and get more out of life. That includes us - the people who work for Unilever, as well as the world around us. Unilever's flexible rewards and benefits are designed to help us all have sustainable households, for whatever life stage you are now and in the future. These include: • Great work environment • Flexible work environment built on trust and freedom • Pension scheme • Employee Assistance Program for you and your family • Well-being hub with access to benefits such as Healthcare, eye tests, health checks, occupational physio Whilst the role is advertised on a full-time basis, we would be happy to discuss possible flexible working options and what this may look like for you. We are a key advocate of well-being and offer a variety of support for our people including hubs, programs, and development opportunities. We strive to achieve a family-friendly and inclusive workplace and to, above all, create possibilities for all. And last but certainly not least - the chance to be a part of a dynamic team with the backing of the globally renowned Unilever brand. Our commitment to Equality, Diversity & Inclusion: Diversity at Unilever is about inclusion, embracing differences, creating possibilities, and growing together for better business performance. We embrace diversity in our workforce. This means giving full and fair consideration to all applicants and continuing the development of all employees regardless of age, disability, gender reassignment, race, religion or belief, gender, sexual orientation, marriage and civil partnership, and pregnancy and maternity. Contact: UnileverSanya Seth Quote job ref: JN-022023-5935615
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
Aliases — catalog
- Informatica (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Data Integration Platform
- Vendor
- Informatica
- License
- proprietary
- Year introduced
- 1993
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Informatica appears frequently in enterprise data-integration and ETL job postings, especially alongside cloud migration and MDM roles; it remains a common hiring keyword rather than a sunset technology.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 114
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
ETL and ELT Tooling Catalog dimension db id 24
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
ETL and ELT Tooling
etl-and-elt-tooling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- DevOps (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Devops Methodology
- Confidence
- 0.97
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: DevOps appears in a large share of software and platform engineering job descriptions, often alongside CI/CD, Kubernetes, and cloud tooling; it is a standard hiring-pipeline keyword rather than a niche specialty.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 922
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
CI/CD Pipeline Platforms Catalog dimension db id 150
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
Deployment and Release Patterns Catalog dimension db id 140
Library dimension (catalog)
Roles linked in library: Cloud Architect
-
Infrastructure as Code Catalog dimension db id 132
Library dimension (catalog)
Roles linked in library: Cloud Architect, DevOps Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Deployment and Release Patterns
deployment-and-release-patterns
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Infrastructure as Code
infrastructure-as-code
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Governance
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Governance
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
All API 3 persistence rows
Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.
| Skill | Tag | Dimension | Skill↔dim | Role↔dim | Outcome | Notes |
|---|---|---|---|---|---|---|
| Informatica | in_db |
ETL and ELT Tooling
etl-and-elt-tooling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| DevOps | in_db |
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| DevOps | in_db |
Deployment and Release Patterns
deployment-and-release-patterns
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| DevOps | in_db |
Infrastructure as Code
infrastructure-as-code
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | Master Data Management | type=Data Governance subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Governance | type=Data Governance subtype=general nature=CONCEPT lifespan=MULTI_YEAR |
nano JD Parser — gpt-4.1-nano click to toggle
Certifications
Show raw JSON
{
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"first_5_words": "For Unilever to remain ruthless",
"last_5_words": "maximizes impact and delivers growth."
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],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Informatica"
},
{
"is_primary": true,
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{
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{
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"nano_parsed": {
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"rejection_reason": null,
"run_id": "fc3d1b12-2b6c-4d63-bcec-f2574b117d97",
"stage3_signals": {
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"alias_match_roles": [
{
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],
"kra_match_roles": [
{
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{
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{
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"sentence": "Guide on the development and delivery of a series of major and minor releases through the year as specified by the roadmap",
"similarity": 0.4691
},
{
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"matched_count": null,
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{
"display_name": "Flutter Developer",
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{
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}
],
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},
{
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{
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{
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{
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{
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},
{
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],
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},
{
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}
]
},
"stage4_decision": {
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"case": "DOMAIN",
"chosen_role": {
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"matched_dimensions": [
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],
"matched_kras": [
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"ensure performance, quality and fit for market needs",
"configuring the MDM match and merge rules",
"manage the wider development team",
"upskill team members on Informatica solution",
"work with the DevOps team on issues relating to the live service",
"review and enhance the technical standards of the implementation",
"ensure information security and personal information policies are abided"
],
"matched_skills": [
"Master Data Management",
"MDM",
"information architecture",
"MDM match and merge rules",
"Informatica",
"DevOps",
"information security",
"personal information policies",
"data governance"
],
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Domain=Data Engineering \u0026 Analytics; The JD centers on master data management, data governance, information architecture, match-and-merge rules, and MDM solution oversight, which best aligns with Data Governance Engineer.",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 8,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": {
"best_kra_similarity": 0.0,
"queue_id": 1386,
"r_and_r_preview": "\u2022 Ability to co-design the information architecture for different MDM solutions\n\u2022 Guide on the development and delivery of a series of major and minor releases through the year as specified by the roa",
"role_display_name": "Data Governance Engineer",
"role_slug": "data-governance-engineer",
"status": "pending"
},
"new_skills_attached": [
{
"is_primary": true,
"queue_id": 19009,
"role_display_name": "Data Governance Engineer",
"role_slug": "data-governance-engineer",
"skill_name": "Master Data Management",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 19010,
"role_display_name": "Data Governance Engineer",
"role_slug": "data-governance-engineer",
"skill_name": "Data Governance",
"status": "pending"
}
],
"queue_entry_id": null,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": null
}
}
API 2 — extract-details
{
"alias_matches": [
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 311,
"existing_alias_text": "Informatica",
"input_term": "Informatica",
"matched_canonical": {
"category_id": 9,
"display_name": "Informatica",
"id": 117,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
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},
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},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
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],
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},
{
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},
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},
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}
],
"input_final_skills": [
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"DevOps",
"Master Data Management",
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],
"input_llm_skills": [
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"DevOps",
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"new_aliases_persisted": 0,
"run_id": "fc3d1b12-2b6c-4d63-bcec-f2574b117d97",
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{
"aliases_in_db": [
{
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}
],
"canonical": {
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"is_extractable": true,
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],
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},
{
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}
],
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},
{
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},
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"merge_log": [],
"placed": null,
"relationships": null,
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"typed": null,
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},
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},
{
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],
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}
API 3 — final-role-output
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{
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},
{
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},
{
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{
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}
],
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],
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{
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{
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],
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{
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],
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],
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},
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