Data Modeler – Business Intelligence

Job Description

Job Summary : As a Data Modeler, you will be responsible for designing, implementing, and optimizing data models that support the organization’s information management and business intelligence needs. You will play a key role in transforming data into meaningful insights by designing data models that ensure efficient storage, retrieval, and integrity of data across various platforms. Key Responsibilities : – Design and develop data models to support the organization’s data and business intelligence requirements. – Collaborate with data architects, data engineers, and stakeholders to ensure data model alignment with business requirements. – Optimize and tune data models for performance and scalability. – Ensure data accuracy, consistency, and integrity by implementing data quality and governance standards. – Participate in data migration and integration projects, ensuring seamless data flow across systems Qualifications : – Bachelor’s or master’s degree in computer science, Information Technology, or a related field. Technical Skills : – Expertise in data modeling tools (e.g., ERwin, Power Designer, SQL Developer Data Modeler). – Proficiency in SQL and database management systems (e.g., Oracle, SQL Server, Snowflake). – Understanding of data warehousing and ETL processes. – Familiarity with data governance and data quality management tools and practices. Soft Skills : – Strong analytical and problem-solving skills. – Effective communication and collaboration skills. – Attention to detail and commitment to data accuracy. Good to Have : – Experience with cloud platforms (e.g., AWS, Azure, GCP). – Knowledge of big data technologies (e.g., Hadoop, Spark). – Exposure to machine learning and advanced analytics. Work Experience : – 5 years of experience in data modeling, data architecture, or related roles. Compensation & Benefits : – Competitive salary and annual performance-based bonuses – Comprehensive health and optional Parental insurance. – Retirement savings plans and tax savings plan. Key Performance Indicator (KPIs) : – Accuracy and Efficiency of Data Models. – Data Model Performance and Query Optimization. – Compliance with Data Governance Standards. – Time to Deliver Data Models for New Requirements. – Stakeholder Satisfaction and Collaboration Effectiveness. Key Result Areas (KRAs) : – Data Model Design: Develop accurate and efficient data models that support business processes. – Data Quality: Ensure data models meet high standards for data accuracy and quality. – Collaboration: Work effectively with cross-functional teams to gather requirements and deliver solutions. – Performance Optimization: Continuously improve data model performance for faster data retrieval. – Documentation and Compliance: Maintain comprehensive documentation and adhere to data governance policies. (ref:hirist.tech)