Data Modeler and Analyst - Sydney

Ayan Infotech

Sydney

On-site

AUD 120,000 - 150,000

Full time

3 days ago
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Job summary

AYAN InfoTech is seeking a Data Modeler and Analyst for a 6-month project based in Sydney. You will contribute to a mature information environment, focusing on detailed logical data models, data lineage, and governance while collaborating with IT and business teams.

The role requires 7+ years in data modelling and analysis, strong SQL skills, and experience with both transactional and analytical systems. The project is based in Sydney with a 6-month contract and extension potential.

Qualifications

  • 7+ years of data modelling and analysis experience.
  • Experience with transactional and analytical systems.
  • Proficient in SQL and data profiling to assess quality metrics.

Responsibilities

  • Create logical data models from business requirements.
  • Review data models with IT and business stakeholders.
  • Map source data elements to target schemas and data models.
  • Assess data quality and data lineage; document metadata and governance activities.
  • Communicate modelling findings and gaps to stakeholders.

Skills

Data modelling
UML modelling
SQL
Data mapping
Metadata management
Data lineage
Data quality
Stakeholder collaboration

Job description

AYAN InfoTech is looking for Data Modeler and Analyst to join an exciting project based in Sydney. The role offers you the opportunity to contribute towards an extremely well structured and mature environment, working on sophisticated enhancement projects.

Role

Data Modeler and Analyst

Location

Sydney

Contract Duration

6 Months with high possible extensions

Experience

7+ Years

Required Capabilities
  • Data Modelling, Conceptual, logical (Entity Relationship) and physical data modelling.
  • Data models review with both IT and business audiences, communicating how the model meets requirements of both existing projects and the overall information architecture and strategy and any relevant deficiencies and gaps.
  • UML modelling using all of the following:
  • Class diagrams
  • Activity diagrams
  • Sequence diagrams
  • Component and package diagrams
  • Analyse and translate current application and data landscapes and future business requirements into detailed logical data models.
  • Strong metadata management (technical and business), incorporating metadata practices into all modelling activities.
  • Analysis of source system including database structures, semi-structured and unstructured data stores.
  • Understanding and assessment of source system schemas; table structures and relationships, primary / foreign keys, indexing, etc.
  • Determining reference data domains and ranges and relationship to transactional data.
  • Data mapping and transformation
  • Mapping of source data elements to target models and data schemas using detailed logical data models.
  • Ability to work with source system SMEs to determine correct mappings, transformations and gaps.
  • Analysis and documentation of source to target data lineage.
  • Data Discovery and Data Quality Assessment
  • Detailed analysis of source system data structures and content to assess "fitness for purpose".
Required Skills and Experience
  • Experience in data analysis and modelling against transactional and analytical systems.
  • Experience in the use of data modelling tools and the management of data modelling repositories and solutions.
  • Experience in using data profiling, using both automated tools and hand coded SQL to determine data quality metrics, constraints, etc.
  • Experience in the delivery of large scale, information management, information governance and analytics solutions
  • At least 5 years of data modelling and analysis experience.
  • Working knowledge of large enterprise relational database management systems comprising of traditional databases (MS SQL Server, Oracle) and cloud based platforms and solutions within AWS…

Contact: 61-(02) 7207 6926 for more details.

Please note we will be able to contact only shortlisted candidates for this role. We thank you in advance for your interest.

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