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Job Description & How to Apply Below
Responsibilities
Analyze and translate business needs to create solution data models. Evaluate current data systems. Work with data analysts, data architects, engineers, and database administrators to design conceptual data models and data flows. Develop standard data coding practices to ensure system-wide consistency. Evaluate changes to existing systems for cross‑compatibility. Implement data strategies and create physical data models. Update and improve local and metadata models.
Assess implemented data systems to identify variances, discrepancies and efficiency gaps. Troubleshoot and optimize data systems. Communicate with internal or external stakeholders to provide guidance, direction and MIS‑related information.
- Strong management skills.
- Strong analytical and problem‑solving skills to effectively design data solutions.
- High attention to detail and commitment to delivering high‑quality work.
- Excellent communication and teamwork skills to collaborate with cross‑functional teams.
- Ability to manage time effectively and prioritize tasks in a dynamic work environment.
- Digital logic skills to clean and organize unstructured data.
- Solid understanding of computer architecture and organization to maximize data processing efficiency.
- Knowledge of data representation techniques for effective data gathering, manipulation, and analysis.
- Understanding of memory architecture to balance speed, durability, reliability, and cost‑effectiveness without compromising data integrity.
- Familiarity with the Erwin data modeling tool.
- Ability to adapt to new data modeling methodologies.
- Proficiency in SQL and its implementation.
- Hands‑on experience with database systems, including RDBMS capable of handling large‑scale data efficiently.
- Bachelor's or Master’s degree in Computer Science, Information Technology, or a related field.
- Demonstrated expertise in working with Databricks for data processing and analysis.
- Experience implementing and optimizing data solutions using multiple programming languages in an Azure environment.
- Cloud technology certifications are an added advantage.
- Proven experience managing a technical team.
- 7-10 years of hands‑on experience in data engineering, including developing data pipelines and managing data infrastructure in Azure.
- Strong Python and SQL experience, with exposure to end‑to‑end data product deployment.
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