Data Engineer

Just Now Data Engineer NTT DATA chennaitamilnadu Ai Recommended 0% Match Score

About The Job NTT Data is hiring for the role of Data Engineer!

Key Responsibilities

• Creates data models in a structured data format to enable analysis thereof.
• Designs and develops scalable extract, transformation and loading (ETL) packages from the business source systems and the development of ETL routines to populate data from sources,
• Participates in the transformation of object and data models into appropriate database schemas within design constraints.
• Interprets installation standards to meet project needs and produce database components as required.
• Creates test scenarios and be responsible for participating in thorough testing and validation to support the accuracy of data transformations.
• Accountable for running data migrations across different databases and applications, for example MS Dynamics, Oracle, SAP and other ERP systems.
• Works across multiple IT and business teams to define and implement data table structures and data models based on requirements.
• Accountable for analysis, and development of ETL and migration documentation.
• Collaborates with various stakeholders to evaluate potential data requirements.
• Accountable for the definition and management of scoping, requirements, definition, and prioritization activities for small-scale changes and assist with more complex change initiatives.
• Collaborates with various stakeholders, contributing to the recommendation of improvements in automated and non-automated components of the data tables, data queries and data models.

To Thrive In This Role, You Need To Have

• Seasoned knowledge of the definition and management of scoping requirements, definition and prioritization activities.
• Seasoned understanding of database concepts, object and data modelling techniques and design principles and conceptual knowledge of building and maintaining physical and logical data models.
• Seasoned expertise in Microsoft Azure Data Factory, SQL Analysis Server, SAP Data Services, SAP BTP.
• Seasoned understanding of data architecture landscape between physical and logical data models
• Analytical mindset with excellent business acumen skills.
• Problem-solving aptitude with the ability to communicate effectively, both written and verbal.
• Ability to build effective relationships at all levels within the organization.
• Seasoned expert in programing languages (Perl, bash, Shell Scripting, Python, etc.).

Academic Qualifications And Certifications

• Bachelor's degree or equivalent in computer science, software engineering, information technology, or a related field.
• Relevant certifications preferred such as SAP, Microsoft Azure etc.
• Certified Data Engineer, Certified Professional certification preferred.

Required Experience

• Seasoned experience as a data engineering, data mining within a fast-paced environment.
• Proficient in building modern data analytics solutions that delivers insights from large and complex data sets with multi-terabyte scale.
• Seasoned experience with architecture and design of secure, highly available and scalable systems.
• Seasoned proficiency in automation, scripting and proven examples of successful implementation.
• Seasoned proficiency using scripting language (Perl, bash, Shell Scripting, Python, etc.).
• Seasoned experience with big data tools like Hadoop, Cassandra, Storm etc.
• Seasoned experience in any applicable language, preferably .NET.
• Seasoned proficiency in working with SAP, SQL, MySQL databases and Microsoft SQL.
• Seasoned experience working with data sets and ordering data through MS Excel functions, e.g. macros, pivots.

Required Skills

• Designed and developed scalable ETL pipelines using Azure Data Factory, SAP Data Services, and SQL Analysis Services
• Created structured data models to support analytics and reporting
• Transformed object and data models into optimized database schemas
• Conducted data validation and testing of ETL workflows
• Managed data migrations across MS Dynamics, Oracle, SAP, and other ERP systems
• Collaborated with cross-functional teams to define data structures and models
• Documented ETL processes and migration strategies
• Analyzed and prioritized data requirements with stakeholders
• Recommended enhancements to data models, queries, and table structures
• Ensured compliance with installation standards and best practices