Data Modeler

Role Overview: You will be a part of the infrastructure engineering team at PwC, focusing on designing and implementing secure and robust IT systems to enhance business operations. Your responsibilities will include creating and implementing scalable technology infrastructure solutions, such as network architecture, server management, and cloud computing. Key Responsibilities: - Analyze business needs and translate them into long-term data model solutions. - Evaluate existing data systems and suggest enhancements. - Define rules for data translation and transformation across different models. - Collaborate with the development team to design conceptual data models and data flows. - Establish best practices for data coding to ensure system consistency. - Review modifications to existing systems for cross-compatibility. - Implement data strategies and create physical data models. - Update and optimize local and metadata models. - Utilize canonical data modeling techniques for improved system efficiency. - Evaluate implemented data systems for discrepancies, variances, and efficiency. - Troubleshoot and optimize data systems for optimal performance. Key Requirements: - Proficiency in relational and dimensional modeling (OLTP, OLAP). - Experience with data modeling tools such as Erwin, ER/Studio, Visio, and PowerDesigner. - Strong skills in SQL and database management systems like Oracle, SQL Server, MySQL, and PostgreSQL. - Familiarity with NoSQL databases such as MongoDB and Cassandra, including their data structures. - Hands-on experience with data warehouses and BI tools like Snowflake, Redshift, BigQuery, Tableau, and Power BI. - Knowledge of ETL processes, data integration, and data governance frameworks. - Excellent analytical, problem-solving, and communication skills. Qualifications: - Bachelor's degree in Engineering or a related field. - 5 to 9 years of experience in data modeling or related areas. - 4+ years of practical experience in dimensional and relational data modeling. - Expertise in metadata management and relevant tools. - Proficiency in data modeling tools like Erwin, Power Designer, or Lucid. - Understanding of transactional databases and data warehouses. Additional Company Details: - The company prefers candidates with experience in cloud-based data solutions, such as AWS, Azure, and GCP. - Knowledge of big data technologies like Hadoop, Spark, and Kafka is a plus. - Understanding of graph databases and real-time data processing is beneficial. - Certifications in data management, modeling, or cloud data engineering are desirable. - Strong communication and presentation skills are valued for effective collaboration with diverse teams.,