Data Modeler

2 weeks ago

Sydney, New South Wales, Australia Cognizant Full time

What makes Cognizant a unique place to work? The combination of rapid growth and an international and innovative environment This is creating many opportunities for people like YOU — people with an entrepreneurial spirit who want to make a difference in this world.

At Cognizant, together with your colleagues from all around the world, you will collaborate on creating solutions for the world's leading companies and help them become more flexible, more innovative, and successful.

Moreover, this is your chance to be part of the success story.

Required Skills:

  • Experience working with large data sets, simulation/ optimization and distributed computing tools
  • Demonstrated expertise in data environment development and improvement across a multitude of on premise and cloudbased data sources
  • Demonstrable experience in developing, validating, publishing and maintaining Logical/physical data models
  • Experience using data modelling tools e.g., ErWin
  • Exposure to building data governance and quality frameworks including (data profiling, data catalog, data dictionary, business glossary and data lineage)
  • Experience building and optimizing big data pipelines, architectures and data sets.
  • Experience in working with large datasets, relational databases (SQL), and distributed systems (Hadoop, Spark, Hive) and streamprocessing systems (Spark-Streaming)
  • Experience with objectoriented/object function scripting languages: Python, Scala, etc.
  • Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
  • Experience with AWS cloud services: S3, EC2, EMR, RDS, Redshift and Kinesis

Responsibilities:

  • Understanding business problems and the Digital Factory product roadmap
  • Working with product teams to identify required data / information for their solutions and the existing sources of said data. This includes quality assessment and technical knowledge of data source capabilities (i.e., data capture frequency, known issues, etc.)
  • Working with Product Teams and the Data Integration Engineer to ensure that new data sources deployed for DF products meet data quality requirements
  • Monitors and manages metadata and ensures usefulness of metadata in improving effectiveness and quality of data
  • Work with the Data Domain Owners to understand the Data Domain, Data entities, Data Standard definitions, Data Classification rules and drive Data Quality framework to support enterprise level data architecture.
  • Implements processes and systems to monitor data quality, ensuring production data is always accurate, complete and consistent and available for key stakeholders and downstream business processes.
  • Define and govern data modelling and design standards, tools, best practices, and related development methodologies for the Data Catalog Organization
  • Create logical and physical data models using best practices to ensure high data quality and reduced redundancy
  • Develop and maintain data lineage and source to target mappings to support data platform architecture
  • Ability to coach members of the teams on achieving goals and developing necessary skills to get results
  • Ability to provide leadership in product quality, technical excellence and engineering practices
  • Responsible for establishing and enforcing standards and practices with the software development team.

Next steps

#LI-GC1COGTAG

Employee Status :
Full Time Employee

Shift :
Day Job

Job Posting :
Jan

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