Senior Data Modeler

• We are looking for a Senior Data Modeller
• to support a Microsoft Fabric data platform programme for a large enterprise
• client.

We are building a more

• product-oriented data organisation, where trusted data assets are created once,
• governed properly and reused across business domains. This role will help shape
• the data models that sit at the heart of that approach.
• The successful candidate will work across
• source system onboarding, Fabric Lakehouse and Warehouse design, reusable
• Silver-layer datasets, Gold-layer analytical models and Power BI semantic
• consumption. The role is not limited to drawing data models. It requires
• someone who can understand business processes, challenge unclear definitions,
• define model grain, agree common entities and help engineering teams turn
• source data into trusted, usable data assets.
• This would suit someone with strong
• dimensional modelling experience who has worked on modern cloud data platforms
• and is comfortable operating between business stakeholders, architects,
• engineers, governance teams and BI/reporting users.

What You Will

Be Doing

• The Data Modeller will be involved in the
• design of enterprise and domain-level data models across Microsoft Fabric. This
• includes conceptual, logical and physical modelling for new data sources,
• business domains and reporting use cases.
• A key part of the role will be to help
• define reusable datasets across the Bronze, Silver and Gold layers. Bronze will
• largely reflect raw or source-aligned data. Silver should become the trusted,
• standardised and reusable business-aligned layer. Gold should support
• consumption through reporting, semantic models, dashboards, analytics and
• future AI use cases.
• The role will work closely with Data
• Engineers to define source-to-target mappings, transformation rules, keys,
• relationships, data quality checks and history handling. It will also involve
• working with Analytics Engineers and Power BI teams to make sure downstream
• semantic models are built on consistent and well-understood data structures.
• The candidate will also support the
• definition of common enterprise entities, such as customer, product, supplier,
• location, transaction, order, contract, employee or other client-specific
• business concepts. The exact domains will depend on the systems being
• onboarded, but the principle is the same: create models that are clear,
• reusable and aligned to business meaning.

Key Responsibilities

• ●Design conceptual, logical and
• physical data models for enterprise data onboarding and analytics use cases.
• ●Define modelling patterns for
• Fabric Lakehouse, Fabric Warehouse and Power BI semantic consumption.
• ●Support the implementation of
• Bronze, Silver and Gold data layers using Medallion Architecture principles.
• ●Design conformed dimensions, fact
• tables, reference data structures, master data views and analytics-ready
• datasets.
• ●Define model grain, business keys,
• surrogate keys, relationships, hierarchies and history handling.
• ●Create source-to-target mappings
• and work with engineers to turn modelling designs into working data assets.
• ●Help define reusable Silver-layer
• datasets that are more than cleansed copies of source systems.
• ●Design Gold-layer models around
• reporting, KPIs, business questions and decision-making needs.
• ●Work with domain teams to
• understand business processes, data ownership, key metrics and analytical
• requirements.
• ●Support Power BI semantic model
• design by ensuring data structures are clear, performant and business-friendly.
• ●Document business definitions,
• model assumptions, lineage, data quality rules and known limitations.
• ●Work with governance teams to
• align models with naming standards, glossary terms, metadata and access
• requirements.

Expected

Outputs

• The role is expected to produce practical
• modelling artefacts that can be used by engineers, analysts, architects and
• business teams. Typical outputs include:
• ●Conceptual and logical data
• models.
• ●Physical model designs for Fabric
• Lakehouse and Warehouse.
• ●Entity relationship diagrams.
• ●Dimensional models with facts,
• dimensions and defined grain.
• ●Source-to-target mapping
• documents.
• ●Data product or dataset
• specifications.
• ●Data dictionaries and business
• definitions.
• ●Lineage and dependency
• documentation.
• ●Data quality rule definitions.
• ●Naming standards and modelling
• design patterns.
• ●Inputs into Power BI semantic
• model design.
• ●Model review packs for
• architecture or governance forums.

Requirements

Required

Skills

• The candidate should have strong hands-on
• experience in enterprise data modelling and data warehousing. They should be
• confident with dimensional modelling, including star schemas, facts,
• dimensions, conformed dimensions and slowly changing dimensions.
• Strong SQL is required. The person does
• not need to be a full-time data engineer, but they should be able to read
• transformation logic, understand joins and aggregations, and challenge whether
• the implemented logic matches the intended business model.
• The candidate should understand modern
• cloud data platforms and Lakehouse concepts. Experience with Microsoft Fabric
• is strongly preferred, especially Fabric Lakehouse, Fabric Warehouse, OneLake
• and Power BI semantic models.
• They should also understand the practical
• role of governance in data modelling: naming standards, definitions, ownership,
• lineage, quality expectations, access controls and metadata.

Mandatory Experience

• ●Enterprise data modelling and data
• warehousing.
• ●Conceptual, logical and physical
• data modelling.
• ●Dimensional modelling, including
• facts, dimensions, star schema and conformed dimensions.
• ●Designing analytics-ready datasets
• for BI and reporting.
• ●Strong SQL.
• ●Experience with cloud data
• platforms or modern data lake/lakehouse architectures.
• ●Understanding of Bronze, Silver
• and Gold data layers.
• ●Working with architects, data
• engineers, analysts and business stakeholders.
• ●Documenting data definitions,
• mappings, lineage and model assumptions.

Preferred Experience

• ●Microsoft Fabric.
• ●Fabric Lakehouse and Fabric
• Warehouse.
• ●OneLake.
• ●Power BI semantic models.
• ●Delta Lake.
• ●Microsoft Purview.
• ●Azure data services.
• ●Data product-oriented delivery.
• ●Data quality and metadata
• management.
• ●Agile delivery environments.

Benefits

• Why join us?
• üWork with a
• passionate and innovative team in a fast-paced, growth-oriented environment.
• üGain hands-on
• experience in content marketing with exposure to real-world projects.
• üOpportunity to learn
• from experienced professionals and enhance your marketing skills.
• üContribute to
• exciting initiatives and make an impact from day one.
• üCompetitive stipend
• and potential for growth within the company.
• üRecognized for
• excellence in data and AI solutions with industry awards and accolades.

Employee Benefits

1.Culture

• a.Open Door Policy: Encourages open communication and accessibility to
• management.
• b.Open Office Floor Plan: Fosters a collaborative and interactive work
• environment.
• c.Flexible Working Hours: Allows employees to have flexibility in their
• work schedules.
• d.Employee Referral Bonus: Rewards employees for referring qualified
• candidates.
• e.Appraisal Process Twice a Year: Provides regular performance evaluations
• and feedback.
• 2.Inclusivity and

Diversity

• a.Hiring practices that promote diversity: Ensures a diverse and inclusive
• workforce.
• b.Mandatory POSH training: Promotes a safe and respectful work
• environment.
• 3.Health Insurance and

Wellness Benefits

• a.GMC and Term Insurance: Offers medical coverage and financial
• protection.
• b.Health Insurance: Provides coverage for medical expenses.
• c.Disability Insurance: Offers financial support in case of disability.

4.Child Care &

Parental Leave Benefits

• a.Company-sponsored family events: Creates opportunities for employees and
• theirfamilies to bond.
• b.Generous Parental Leave: Allows parents to take time off after the birth
• or adoption of a child.
• c.Family Medical Leave: Offers leave for employees to take care of family
• members' medical needs.
• 5.Perks and Time-Off

Benefits

• a.Company-sponsored outings: Organizes recreational activities for
• employees.
• b.Gratuity: Provides a monetary benefit as a token of appreciation.
• c.Provident Fund: Helps employees save for retirement.
• d.Generous PTO: Offers more than the industry standard for paid time off.
• e.Paid sick days: Allows employees to take paid time off when they are
• unwell.
• f.Paid holidays: Gives
• employees paid time off for designated holidays.
• g.Bereavement Leave: Provides time off for employees to grieve the loss of
• a loved one.

6.Professional

Development Benefits

• a.L&D with FLEX- Enterprise Learning Repository: Provides access to a
• learning repository for professional development.
• b.Job Training: Provides training to enhance job-related skills.
• c.Professional Certification Reimbursements: Assists employees in
• obtaining professional certifications.
• d.Promote from Within: Encourages internal growth and advancement
• opportunities.