Data Modeler (Business Analyst)

About Us:

At Parkar we are redefining cloud transformation with the power of Microsoft Azure and AWS platforms. Our commitment to aligning with industry-leading cloud technologies enables us to deliver tailored best-in-class solutions that drive tangible results for our clients.

With over a decade of experience and more than 100 enterprise engagements across diverse industries we specialize in empowering businesses to innovate and scale. From AIOps to Generative AI and advanced Machine Learning our expertise spans the technologies that shape tomorrows enterprises.

As a Microsoft Gold Partner we boast over 125 Azure certifications and a track record of 400 successful projects powered by our team of 200 skilled engineers. Whether its data analytics DevOps automation or application development Parkar is dedicated to achieving each clients unique transformation goals with agility precision and a relentless pursuit of excellence.

Vector is our flagship platform built on the latest in IT and AI technology to empower organizations to work smarter and stay ahead in a fast-changing digital world. It streamlines digital operations with intelligent automation and seamless cloud integration. With features like real-time monitoring early problem detection and scalable flexibility Vector helps reduce costs boost reliability and drive continuous innovation.

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Role Overview:

The data modeler plays a crucial role in designing developing and maintaining data models to support efficient data management and analytics within the organization. This role is essential in optimizing data architecture translating business initiatives into robust data models and enhancing data integrity availability and performance. The data modeler is responsible for developing conceptual logical and physical data models.
As a data analyst this role interprets and analyses complex datasets to provide insights and support data-driven decision making within an organization. This role works alongside engineers modelers and business executives to gather and transform data conduct statistical analyses and create visualizations and reports that will contribute to identifying trends patterns and opportunities that drive business initiatives.

Responsibilities:

• Understand business requirements and translate them into data requirements.
• Analyze existing data structures and determine gaps if any to meet new requirements across all ongoing initiatives.
• Actively participate in all ongoing initiatives related to the data and analytics ecosystem including capital projects operational projects and proof of concept work.
• Profile source data by retrieving and gathering raw data from various internal and external source systems to identify trends patterns and quality issues.
• Design optimize and maintain conceptual logical and physical data models to support efficient data management and analytics within the organization.
• Collaborate with data architects data engineers report developers AI/ML engineers and business stakeholders/executives.
• Map out data personas and consumer profiles to ensure a better understanding of customer needs.
• Design create and implement logical and physical data models for both IT and business solutions to capture the structure relationships and constraints of relevant datasets.
• Build and operationalize complex data solutions correct problems apply transformations and recommend data cleansing/quality solutions.
• Effectively collaborate and communicate with various stakeholders to understand data and business requirements and translate them into data models.
• Create entity-relationship diagrams (ERDs) data flow diagrams and other visualization tools to represent data models.
• Collaborate with database administrators and software engineers to implement and maintain data models in databases data warehouses and data lakes.
• Develop data modeling best practices and use these standards to identify and resolve data modeling issues and conflicts.
• Conduct performance tuning and optimization of data models for efficient data access and retrieval.
• Incorporate core data management competencies including data governance data security and data quality.

Requirements:

• Bachelors degree in related field.
• Hands-on experience in data gathering profiling data modeling and data analysis.
• Expert knowledge of data modeling concepts methodologies and best practices & proficiency in data modeling tools. Familiarity with dimensional modeling and data warehousing concepts
• Expert level of proficiency in designing SQL queries and Python scripts.
• Hands-on relational dimensional and analytical project experience using RDBMS (SAP Oracle SQL Server) NoSQL (Cassandra Mongo) data platform technologies and ETL.
• Robust experience with databases like SAP Oracle SQL Server etc. and Big Data/Cloud platforms like Microsoft Azure Google Big Query Databricks AWS Cloudera etc.
• Experience with unstructured semi-structured and structured data.
• Experience with Business Intelligence/Data visualization and Reporting tools such as Power BI.
• Expert knowledge of statistical analysis techniques and concepts for both descriptive and inferential statistics.
  Knowledge of data visualization is the best practice to effectively communicate insights.

Education:

• Bachelors degree in computer science engineering or similar domain.