Job Description

Key Responsibilities: Design and develop conceptual, logical, and physical data models to support business requirements and data architecture standards. Collaborate with business analysts, data architects, and data engineers to understand data requirements and translate them into effective data models. Ensure data models are aligned with industry best practices, data governance policies, and regulatory compliance requirements. Conduct data analysis and profiling to identify data quality issues, anomalies, and inconsistencies. Optimize data models for performance, scalability, and data retrieval efficiency. Work closely with database administrators and developers to implement data models in database management systems. Document data model designs, data flows, and metadata for effective communication and reference. Convert the Oracle SQL statements into HQL scripts for data extraction, transformation, and loading in the Hive environment. Conduct performance tuning and optimization of the HQL scripts to enhance query efficiency and data processing speed. Perform data modelling reviews and provide recommendations for improvement. Stay up-to-date with emerging trends, technologies, and best practices in data modelling and database design. Participate in data governance initiatives and contribute to the overall data management strategy of the organization. Qualifications and Skills: Bachelor's or Master's degree in Computer Science, Information Systems, or a related field. 5+ years of experience in data modelling, data warehousing, and ETL processes Strong understanding of data modelling concepts (e.g., entity-relationship modelling, dimensional modelling). Experience in designing data models for relational databases and familiarity with database management systems (e.g., Oracle, SQL Server, MySQL). Knowledge of big data environments such as Apache Hadoop, Apache Spark, Hive, or Apache Cassandra to design data models suitable for distributed and scalable processing. Experience in using Version control systems like Git enable data modelers to manage changes, track revisions, and collaborate effectively on data model designs. Knowledge of data governance principles and practices. Excellent analytical and problem-solving skills. Strong communication and collaboration skills to work effectively with cross-functional teams. Ability to prioritize tasks and work on multiple projects simultaneously. Attention to detail and a commitment to producing high-quality deliverables.