Technology, Information and Internet

Cypher Consulting Europe

1-10

Poland



## Tasks

● Be able to explain the positioning of data modelling in relation to business process, top-down and bottom up modelling

● Understand bus matrix definition usage when communicating to the business and building data platforms

● Have performed data discovery, understand grain, data relationships and any data quality issues

● Make recommendations to optimise the model to ensure performance against data infrastructure, particularly Synapse

● Capture model metadata including, semantics, Identify relationships, keys, characteristics and properties

● Understand different file formats e.g. parquet, json, xml, csv, avro, protobuf, having used them as data sources for modelling on previous projects

● Have prepared and managed database objects, data flow diagrams, mapping specifications

● Have developed and deployed DDLs in the target environment

● Be familiar with practices of engineering teams e.g. how data pipelines will use mapping and DDLs

produced by modellers

● Be familiar with metadata-driven approaches to the creation of data pipelines

● Have worked with reference data models including Teradata, ARDM, and Oracle Retail.

## Requirements

● Large scale data transformation, stakeholder management and be proactive in delivery

● Retail, off the shelf Retail Data Sources, and have previously modelled retail concepts across multiple data domains

● Data Vault 2.0 Modelling (essential), Relational Modelling in 3NF, Dimensional Modelling, Conceptual Modelling, having previously delivered on a transformational programme with Data Vault 2.0

● Projects modelling PII, and sensitive data classifications

● Working with the business, architecture, and engineering community

● Multiple modelling tools e.g. ERWIN, Idera, EA Sparx, Powerdesigner, Wherescape, SQLDBM, being able to make a recommendation of their preferred tool when modelling Data Vault and explain why.

● Platform components include Azure, Azure Data Lake, Azure Data Factory, Azure Purview, Azure Synapse, and PowerBI. Any understanding of pyspark is a bonus

● Working on Agile projects, being able to estimate and justify thinking

● Been part of a community of practice for modelling, engineering, and be comfortable explaining modelling and design decisions

Freelance

<h2 id="tasks">Tasks</h2>
● Be able to explain the positioning of data modelling in relation to business process, top-down and bottom up modelling
● Understand bus matrix definition usage when communicating to the business and building data platforms
● Have performed data discovery, understand grain, data relationships and any data quality issues
● Make recommendations to optimise the model to ensure performance against data infrastructure, particularly Synapse
● Capture model metadata including, semantics, Identify relationships, keys, characteristics and properties
● Understand different file formats e.g. parquet, json, xml, csv, avro, protobuf, having used them as data sources for modelling on previous projects
● Have prepared and managed database objects, data flow diagrams, mapping specifications
● Have developed and deployed DDLs in the target environment
● Be familiar with practices of engineering teams e.g. how data pipelines will use mapping and DDLs
produced by modellers
● Be familiar with metadata-driven approaches to the creation of data pipelines
● Have worked with reference data models including Teradata, ARDM, and Oracle Retail.
<h2 id="requirements">Requirements</h2>
● Large scale data transformation, stakeholder management and be proactive in delivery
● Retail, off the shelf Retail Data Sources, and have previously modelled retail concepts across multiple data domains
● Data Vault 2.0 Modelling (essential), Relational Modelling in 3NF, Dimensional Modelling, Conceptual Modelling, having previously delivered on a transformational programme with Data Vault 2.0
● Projects modelling PII, and sensitive data classifications
● Working with the business, architecture, and engineering community
● Multiple modelling tools e.g. ERWIN, Idera, EA Sparx, Powerdesigner, Wherescape, SQLDBM, being able to make a recommendation of their preferred tool when modelling Data Vault and explain why.
● Platform components include Azure, Azure Data Lake, Azure Data Factory, Azure Purview, Azure Synapse, and PowerBI. Any understanding of pyspark is a bonus
● Working on Agile projects, being able to estimate and justify thinking
● Been part of a community of practice for modelling, engineering, and be comfortable explaining modelling and design decisions

Data Modeler

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