Key Accountabilities

• Spearhead the advancement of our data and analytics capabilities within the R&D node of our enterprise data mesh by implementing the architectural blueprints for various Data Platforms.
• Developing and implementing an organizational data strategy in line with business processes. The strategy includes data model designs, database development standards, implementation and management of data warehouses and data analytics systems
• Identifying data sources, both internal and external, and working out a data management plan aligned with organizational data strategy
• Coordinating and collaborating with cross-functional teams, stakeholders, and vendors for the smooth functioning of the enterprise data ecosystem
• Guide the technical direction of data projects and initiatives.
• Ensure best practices in data engineering and analytics are followed. Integrating technical functionality, ensuring data accessibility, accuracy, and security
• Conducting a continuous audit of data management system performance, refine whenever required, and report immediately any breach or loopholes to the stakeholders

Experience/Previous Jobs Required for the Job

• Experience in D&A platforms. Includes analysis and translation of requirements into technical specifications and who directs the day-to-day implementation activities of the DevOps team. Should be hands-on on all specified technology
• 9+ years of experience in Big Data, data warehouse, data analytics projects, and/or any Information Management related projects
• Prior experience building large scale enterprise data architectures using commercial and/or open-source Data Analytics technologies
• Ability to produce client ready solution architecture, business understandable presentations and effective communication skills to lead and run workshops
• Data modelling and architecting skills including solid foundation in data warehousing concepts, data normalization, and dimensional data modelling such as OLAP, or data vault.
• Understanding of predictive modeling, NLP and text analysis, Machine Learning
• Good fundamentals around security integration including Kerberos authentication, SAML and data security and privacy such as data masking and tokenization techniques
• Good knowledge in DevOps engineering using Continuous Integration/ Delivery tools
• An in-depth understanding of AWS Cloud solutions
• Experienced in integrating into legacy systems and COTS solutions
• Candidates ideally have experience in the below tools:
  • Data Ingestion – Snaplogic, Glue, Lambda
  • Storage – S3
  • Processing – Databricks
  • DWH – Redshift, Databricks SQL Warehouse
  • Databases – RDS
  • Language – Python (pyspark), SQL (sparksql), Java, R
  • BI Tools – PowerBI, DASH, Spotfire, Qlik
  • Catalogue – Glue catalog, Unity Catalog
  • Streaming – Kafka, Eventhub
  • AI/ML – MLOps, Sagemaker
  • Storage /  Dataframe work – S3, Deltalake, Iceberg, Parquet

Critical knowledge and education required for the job

• University bachelor’s degree in science, Technology, Engineering or Mathematics (STEM)
• Fluency in English
• Strong customer focus, communication, teamwork, and negotiation skills
• Experience implementing data first solutions
• In depth technical experience, ideally AWS certified