Senior Data Modeller

Job Description:

We are looking for a talented and experienced Senior Data Modeler to join our growing team. As a Senior Data Modeler, you will be responsible for designing, implementing, and maintaining data models to enhance data quality, performance, and scalability. You will collaborate with cross-functional teams including data analysts, architects, and business stakeholders to ensure that the data models align with business requirements and drive efficient data management.

Key Responsibilities:

• Design, implement, and maintain data models that support business requirements, ensuring high data quality, performance, and scalability.
• Collaborate with data analysts, data architects, and business stakeholders to align data models with business needs.
• Leverage expertise in Azure, Databricks, and data warehousing to create and manage data solutions.
• Manage and optimize relational and NoSQL databases such as Teradata, SQL Server, Oracle, MySQL, MongoDB, and Cassandra.
• Contribute to and enhance the ETL processes and data integration pipelines to ensure smooth data flows.
• Apply data modeling principles and techniques, such as ERD and UML, to design and implement effective data models.
• Stay up-to-date with industry trends and emerging technologies, such as big data technologies like Hadoop and Spark.
• Develop and maintain data models using data modeling tools such as ER/Studio and Hackolade.
• Drive the adoption of best practices and standards for data modeling within the organization.

Skills and Qualifications:

• Minimum of 6+ years of experience in data modeling, with a proven track record of implementing scalable and efficient data models.
• Expertise in Azure and Databricks for building data solutions.
• Proficiency in ER/Studio, Hackolade, and other data modeling tools.
• Strong understanding of data modeling principles and techniques (e.g., ERD, UML).
• Experience with relational databases (e.g., Teradata, SQL Server, Oracle, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra).
• Solid understanding of data warehousing, ETL processes, and data integration.
• Familiarity with big data technologies such as Hadoop and Spark is an advantage.
• Industry Knowledge: A background in supply chain is preferred but not mandatory.
• Excellent analytical and problem-solving skills.
• Strong communication skills, with the ability to interact with both technical and non-technical stakeholders.
• Ability to work well in a collaborative, fast-paced environment.