Job Description

Specialist – Data Architect

Technologies & Skills:

Experience: 6 - 9 years

Qualification: BE, Statistics, Mathematics degree

Specialization:

  1. Bachelor’s in computer science/Engineering, Statistics, Mathematics, or related quantitative degree
  2. 6-9 years of professional experience as a Data Architect, Data Engineer or related role developing conceptual, logical, and preliminary physical models for an enterprise
  3. 4+ years of experience in Industry 4.0 initiatives and/or other aspects of corporate data management, e.g. Data Governance, Data Quality, Data Security, AI/ML, Data DevOps
  4. Experience with programming languages like Python, Java, SQL and Cloud technologies
  5. Deep experience with database structure systems and data mining
  6. Knowledge of developing and using data standards comprising the format, representation, definition, structuring, manipulation, tagging, transmission, use, and management of data
  7. Experience developing and using metadata guidelines to tag data and use the tags as part of a data management strategy
  8. Experience assessing data solutions for compliance and conformance with guidelines and policies
  9. Understanding of the use and maintenance of data dictionaries, data models, and data maps in an enterprise business software environment
  10. Provide leadership for complex projects throughout the development of project work plans, milestone tracking, and coordination of efforts
  11. Aptitude to learn new technologies and communicate the business value of new technology solutions
  12. Excellent organizational and analytical abilities, and able to compile and organize statistical information retrieved and present findings to management

 

Responsibilities:

  1. Develop best in class capability of deploying self-running and learning framework for Data Science, ML/DL model across cloud platform
  2. Provide strategic direction and technical expertise to meet data architecture needs
  3. Contribute to the development of data policies, governance and implementation plans, and conceptual and logical data models
  4. Work to assess data architectures to determine overall effectiveness and compliance with data strategy, enterprise requirements, and objectives
  5. Review and comment on data solutions designed by IT project teams, and support requirements development
  6. Research the implementation of data standards (DMBOK) for interoperability, quality, and entity and data attributes
  7. Play a key role in cloud migration strategy with focus on single/multi cloud, best possible tools/service on cloud, design architecture
  8. Should be able to leverage Dev ops environment like GitHub, Docker, and Kubernetes etc. to deploy/orchestrate the models
  9. Establish rail roads of continuous data flow and transmission of insights to business especially in real time environment.
  10. Help come up with framework on cost optimization while running various process on cloud basis analytics job execution
  11. Instrumental in designing dev ops capability of the analytics group, which can lead to making “data as first citizen” in the organization
  12. Regular interaction with technology, analytics and business stakeholders to ensure the analytics use case pipeline are prioritised basis organization priority and impact
  13. Enforcing data architecture standards, procedures and policies to ensure consistency across different program and project implementations