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Sr.Data Modeler

Convene Inc.

Remote • Today

Easy Apply

Contract, Third Party

Depends on Experience

Job Details

Skills

Summary

About Convene Inc.

Convene, Inc. is a Tampa based, award-winning technology services organization with offices and resources throughout the US, Mexico, and India. We have successful, referenceable customers, competitive benefits, and high-growth opportunities.

Senior Data Modeler
Purpose of the Position
The Senior Data Modeler will be a key contributor within the Data Architecture Team of the Enterprise Data Solutions Department, responsible for designing and governing the Silver layer of the enterprise data lakehouse built on Medallion Architecture. This role translates data from operational systems into standardized, integrated, and analytics-ready enterprise entities, using normalized Third Normal Form (3NF) as the primary modeling approach, supplemented by Data Vault 2.0 and other patterns where appropriate.
The Senior Data Modeler will partner closely with Data Architects, Data Engineers, Business Analysts, Data Governance, and source-system SMEs to ensure models are accurate, traceable, scalable, and implementation-ready, and that they reliably support downstream Gold-layer reporting and analytics.
Primary Duties and Responsibilities

Silver Layer Data Modeling – Design, develop, and maintain conceptual, logical, and physical data models for the Silver layer of the enterprise data lakehouse built on Medallion Architecture.
Normalized (3NF) Entity Design – Design 3NF entities for master, reference, transactional, association, episode, and event-history data.
Data Vault 2.0 Design – Apply hubs, links, satellites, business keys, and historization where appropriate.
Source Data Profiling – Profile source data to confirm grain, keys, relationships, cardinality, completeness, code domains, and data-quality issues.
Source-to-Target Mapping – Create attribute-level mappings covering transformations, data types, nullability, key behavior, historization, DQ rules, and PII classification.
Key Design – Define surrogate keys, alternate keys, source-system crosswalks, and unresolved foreign-key handling.
Historization – Recommend appropriate patterns, including SCD Type 1, selective SCD Type 2, lifecycle episodes, and append-only events.
Canonical Modeling – Design reusable canonical models capable of integrating multiple source systems without major redesign.
Standards & Governance – Define and enforce standards for naming, reference data, lineage, audit, retention, deletion, and data quality.
Implementation Review – Review implementation SQL and pipelines to ensure alignment with approved models.
Model Management – Maintain models, definitions, relationships, and documentation in the enterprise modeling tool.
Gold Layer Support – Support downstream dimensional models and KPI reporting without embedding report-specific logic in Silver.
Cross-Functional Collaboration – Partner with data architects, data engineers, business analysts, governance teams, and source-system SMEs.

Education/Experience

Required – Bachelor's degree in Information Systems, Computer Science, or a related field.
Required – 5–10 years of experience in data modeling, data architecture, or data engineering.
Required – Minimum 2–3 years of hands-on experience with Medallion Architecture (Bronze / Silver / Gold).
Required – Strong expertise in Third Normal Form (3NF) and normalized relational modeling.
Required – Strong working knowledge of Data Vault 2.0.
Required – Advanced SQL skills and experience profiling large operational datasets.
Required – Experience modeling data for cloud lakehouse or modern data-platform environments.
Preferred – Experience with SaaS-based data modeling tools such as SQLDBM.

Associated Knowledge, Skills & Abilities
REQUIRED

Architecture: Medallion Architecture, cloud lakehouse design.
Data Modeling: 3NF, Data Vault 2.0, conceptual/logical/physical modeling, SCD Type 1 and Type 2.
Keys & Integrity: Business, surrogate, and alternate keys; referential integrity.
Entity Types: Master, reference, transaction, bridge, association, episode, and event entities.
Data Management: Source profiling, source-to-target mapping, data lineage, DQ rules.
Tools: Advanced SQL.
Collaboration: Strong documentation, communication, and stakeholder management; ability to distinguish source-system behavior from confirmed business meaning.

PREFERRED

Tools: SaaS-based modeling tools such as SQLDBM; ERwin or ER/Studio also considered.
Platforms: Databricks, Delta Lake, Spark SQL, Unity Catalog.
Source Systems: ERP, CRM, SIS, LMS, or financial systems integration.
Governance: Metadata management, PII protection, data-quality frameworks.
Processing: CDC, schema evolution, retention policies, incremental processing.
Downstream: Gold-layer dimensional models and enterprise KPI reporting.

Expected Deliverables

Approved conceptual, logical, and physical Silver-layer models.
Entity inventory and relationship matrices.
Attribute-level source-to-target mappings.
Source-data profiling findings and exception documentation.
Key, historization, retention, lineage, and DQ specifications.
Implementation-ready models and documentation supporting review, traceability, and future source integration.

Success Measures

Silver entities have clearly defined and tested grains.
Source and business keys are supported by profiling evidence.
Relationships and optionality are documented and validated.
Historical behavior is handled consistently and intentionally.
Models can integrate additional source systems without major redesign.
Data engineers can implement models without inventing missing business or technical rules.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 10429112
Position Id: 26-00119
Posted 3 hours ago

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Job Details

Skills

Summary

About Convene Inc.

Silver Layer Data Modeling – Design, develop, and maintain conceptual, logical, and physical data models for the Silver layer of the enterprise data lakehouse built on Medallion Architecture.
Normalized (3NF) Entity Design – Design 3NF entities for master, reference, transactional, association, episode, and event-history data.
Data Vault 2.0 Design – Apply hubs, links, satellites, business keys, and historization where appropriate.
Source Data Profiling – Profile source data to confirm grain, keys, relationships, cardinality, completeness, code domains, and data-quality issues.
Source-to-Target Mapping – Create attribute-level mappings covering transformations, data types, nullability, key behavior, historization, DQ rules, and PII classification.
Key Design – Define surrogate keys, alternate keys, source-system crosswalks, and unresolved foreign-key handling.
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Canonical Modeling – Design reusable canonical models capable of integrating multiple source systems without major redesign.
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Implementation Review – Review implementation SQL and pipelines to ensure alignment with approved models.
Model Management – Maintain models, definitions, relationships, and documentation in the enterprise modeling tool.
Gold Layer Support – Support downstream dimensional models and KPI reporting without embedding report-specific logic in Silver.
Cross-Functional Collaboration – Partner with data architects, data engineers, business analysts, governance teams, and source-system SMEs.

Education/Experience

Required – Bachelor's degree in Information Systems, Computer Science, or a related field.
Required – 5–10 years of experience in data modeling, data architecture, or data engineering.
Required – Minimum 2–3 years of hands-on experience with Medallion Architecture (Bronze / Silver / Gold).
Required – Strong expertise in Third Normal Form (3NF) and normalized relational modeling.
Required – Strong working knowledge of Data Vault 2.0.
Required – Advanced SQL skills and experience profiling large operational datasets.
Required – Experience modeling data for cloud lakehouse or modern data-platform environments.
Preferred – Experience with SaaS-based data modeling tools such as SQLDBM.

Associated Knowledge, Skills & Abilities
REQUIRED

Architecture: Medallion Architecture, cloud lakehouse design.
Data Modeling: 3NF, Data Vault 2.0, conceptual/logical/physical modeling, SCD Type 1 and Type 2.
Keys & Integrity: Business, surrogate, and alternate keys; referential integrity.
Entity Types: Master, reference, transaction, bridge, association, episode, and event entities.
Data Management: Source profiling, source-to-target mapping, data lineage, DQ rules.
Tools: Advanced SQL.
Collaboration: Strong documentation, communication, and stakeholder management; ability to distinguish source-system behavior from confirmed business meaning.

PREFERRED

Tools: SaaS-based modeling tools such as SQLDBM; ERwin or ER/Studio also considered.
Platforms: Databricks, Delta Lake, Spark SQL, Unity Catalog.
Source Systems: ERP, CRM, SIS, LMS, or financial systems integration.
Governance: Metadata management, PII protection, data-quality frameworks.
Processing: CDC, schema evolution, retention policies, incremental processing.
Downstream: Gold-layer dimensional models and enterprise KPI reporting.

Expected Deliverables

Approved conceptual, logical, and physical Silver-layer models.
Entity inventory and relationship matrices.
Attribute-level source-to-target mappings.
Source-data profiling findings and exception documentation.
Key, historization, retention, lineage, and DQ specifications.
Implementation-ready models and documentation supporting review, traceability, and future source integration.

Success Measures

Silver entities have clearly defined and tested grains.
Source and business keys are supported by profiling evidence.
Relationships and optionality are documented and validated.
Historical behavior is handled consistently and intentionally.
Models can integrate additional source systems without major redesign.
Data engineers can implement models without inventing missing business or technical rules.

Dice Id: 10429112
Position Id: 26-00119
Posted 3 hours ago

Fitment

Dice Job Match Score™

To see how well you match this job, please log in or create an account.

Once logged in, be sure to complete your profile to get the most accurate match score.

Create job alert

Never miss an opportunity! Create an alert based on the job you applied for.

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