Work with large, complex data sets that meet both functional and non-functional business requirements.
Build the necessary infrastructure for extracting, transforming, and loading data from various sources. Using technologies like Azure and SQL.
Implement / Deploy large, structured and unstructured databases based on scalable cloud infrastructures.
Port data across data-sources /DB systems to improve performance, scalability or to facilitate analytics.
Develop technical solutions which combine disparate information to create meaningful insights for business, using Big-data architectures (supportive role along with Data Architect)
Stay curious and enthusiastic about using related technologies to solve problems and enthuse others to see the benefit in business domain
Qualification: Bachelor's or Master's in Computer Science & Engineering, or equivalent. Professional Degree in Data Science, Engineering is desirable.
Experience level: At least 4 - 5 years hands-on experience in the area of DB; with working experience on Data Engineering, Data Analytics and Data visualization in multiple projects.
Desired Knowledge & Experience:
Expert knowledge and multi-year (4+) experience on data transformation, data bases, data governance and data quality management.
Experience in conventional DB technologies (RDBMS, Object Oriented)
Experience in using query languages such as SQL
Hands-on expertise in big data technologies such as Azure Databricks, Spark and distributed databases (e.g. Teradata).
Working knowledge of Azure cloud-based Data Storage and Services like (Azure BLOB, AZURE Databricks, Azure Data Factory, etc) is preferred.
Strong knowledge on Extract Transform & Load concept (Azure Data Factory)
Working knowledge of any reporting/BI tool (e.g. Qlik, Tableau, PowerBI, etc)
Knowledge of Cloud technologies and frameworks in Microsoft Azure or Amazon AWS environment is desirable.
Well-versed in relational database design and experience with processing and managing large data sets (multiple TB scale). (e.g. T-SQL, Microsoft SQL, Oracle)
Exceptional knowledge of data warehousing solutions (e.g Teradata, Snowlflake)
Exceptional knowledge in Data Warehousing concepts (Data Modelling, STAR Schema, Snowflake Schema and various Data Warehousing concepts)
Good know-how & experience on Dataops (Data Orchestration / Workflow management & Monitoring Systems) and suggest improvements / inputs for CI/CD.
Sound knowledge in programming languages like Python, R will be an added advantage.
Experience with NoSQL databases such as MongoDB, Cassandra, HBase, is desirable.
Strong inclination towards working in any Data projects.
Strong written/communication skill to be work with partners along the globe.
Required Soft skills & Other Capabilities:
Great attention to detail and good analytical abilities.
Good planning and organizational skills
Collaborative approach to sharing ideas and finding solutions
Ability to work independently and also in a global team environment.
