Senior Associate_Data Modeler-Tech Ops PwC Acceleration Center India

5.0 - 9.0 years

0 Lacs

karnataka

On-site

At PwC, the infrastructure team focuses on designing and implementing secure IT systems that support business operations. The primary goal is to ensure the smooth functioning of networks, servers, and data centers to enhance performance and minimize downtime. In the infrastructure engineering role at PwC, you will be tasked with creating robust and scalable technology infrastructure solutions for clients. This will involve working on network architecture, server management, and cloud computing. As a Data Modeler, we are seeking candidates with a solid background in data modeling, metadata management, and data system optimization. Your responsibilities will include analyzing business requirements, developing long-term data models, and ensuring the efficiency and consistency of our data systems. Key areas of expertise for this role include: - Analyzing and translating business needs into long-term data model solutions. - Evaluating existing data systems and suggesting enhancements. - Defining rules for translating and transforming data across various models. - Collaborating with the development team to create conceptual data models and data flows. - Establishing best practices for data coding to maintain consistency within the system. - Reviewing modifications of existing systems for cross-compatibility. - Implementing data strategies and developing physical data models. - Updating and optimizing local and metadata models. - Utilizing canonical data modeling techniques to improve data system efficiency. - Evaluating implemented data systems for variances, discrepancies, and efficiency. - Troubleshooting and optimizing data systems for optimal performance. - Demonstrating strong expertise in relational and dimensional modeling (OLTP, OLAP). - Using data modeling tools like Erwin, ER/Studio, Visio, PowerDesigner effectively. - Proficiency in SQL and database management systems (Oracle, SQL Server, MySQL, PostgreSQL). - Understanding of NoSQL databases (MongoDB, Cassandra) and their data structures. - Experience with data warehouses and BI tools (Snowflake, Redshift, BigQuery, Tableau, Power BI). - Familiarity with ETL processes, data integration, and data governance frameworks. - Strong analytical, problem-solving, and communication skills. Qualifications for this position include: - A Bachelor's degree in Engineering or a related field. - 5 to 9 years of experience in data modeling or a related field. - 4+ years of hands-on experience with dimensional and relational data modeling. - Expert knowledge of metadata management and related tools. - Proficiency with data modeling tools such as Erwin, Power Designer, or Lucid. - Knowledge of transactional databases and data warehouses. Preferred Skills: - Experience in cloud-based data solutions (AWS, Azure, GCP). - Knowledge of big data technologies (Hadoop, Spark, Kafka). - Understanding of graph databases and real-time data processing. - Certifications in data management, modeling, or cloud data engineering. - Excellent communication and presentation skills. - Strong interpersonal skills to collaborate effectively with various teams.,

Posted 11 hours ago

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Data Modeler PwC Acceleration Center India

5.0 - 9.0 years

0 Lacs

karnataka

On-site

At PwC, our team in infrastructure is dedicated to designing and implementing secure and robust IT systems that facilitate business operations. We focus on ensuring the smooth functioning of networks, servers, and data centers to enhance performance and reduce downtime. As part of the infrastructure engineering team at PwC, your role will involve creating and implementing scalable technology infrastructure solutions for our clients. This will encompass tasks such as network architecture, server management, and experience in cloud computing. We are currently seeking a Data Modeler with a solid background in data modeling, metadata management, and optimizing data systems. In this role, you will be responsible for analyzing business requirements, developing long-term data models, and maintaining the efficiency and consistency of our data systems. 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 to ensure cross-compatibility. - Implement data strategies and create physical data models. - Update and optimize local and metadata models. - Utilize canonical data modeling techniques to improve system efficiency. - Evaluate implemented data systems for discrepancies, variances, and efficiency. - Troubleshoot and optimize data systems to achieve 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. Preferred Skills: - Experience in cloud-based data solutions, such as AWS, Azure, and GCP. - Knowledge of big data technologies like Hadoop, Spark, and Kafka. - Understanding of graph databases and real-time data processing. - Certifications in data management, modeling, or cloud data engineering. - Strong communication and presentation skills. - Excellent interpersonal skills to collaborate effectively with diverse teams.,

Posted 2 days ago

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