CLOUD DATA & ANALYTICS ENGINEER

As a Cloud Data & Analytics Engineer, you will:

Design and architect several functional layers, of parametric design framework (workflows, data management, AI/ML, Integration with other systems).
Work closely with a team of IT Business partner, Network Security, Infrastructure teams & technical experts.
Create & document high- & low-level designs/frameworks for all components of parameterized simulation & automation factory.
Optimize Cloud costs by defining / tracking cost plans, reserved Instances, enterprise saving plans on widely used Public & Hybrid Cloud platforms built on AWS, Azure, Google, etc.
Develop and maintain cloud infrastructure capacity and demand forecasts – incl. day to day cost monitoring and tracking of cloud capacity & resource mgmt. for all services.
Liaise with multiple stakeholders (across IT, finance, business functions) and proactively identify opportunities for service improvement.
Identify & robustly validate potential benefits of new technology in use cases.
Analytics solutions delivery in Agile DevOps methodology on Business Intelligence and Data Visualizations systems.

Extensive knowledge on ETL Processes, Data Modelling & Data Profiling.
Design, Implementation on End-to-end BI Systems build & DV Applications launch.
Relational & Dimensional Modelling on Big Data Systems and Data Lakes.
Agile/scrum in software development and knowledge of systems development lifecycles.
Integration technologies/architecture, REST API, Cloud based API’s, Secure integrations. & microservices.
DWH designing on Cloud & RDMS like Postgres DB, Amazon RDS, Azure Data Factory, Oracle, SQL server, etc.
Strong Data analysis of any visualization tools like Cognos Analytics, Cognos Controller, Planning Analytics, Qlik Sense, Power BI, Tableau.
Good understanding of cloud cost estimation & billing on cloud platforms (incl. impact of usage patterns on TCO).
Capacity forecasting and workflow management in a large service operations environment. Familiarity with monitoring and reporting tools/APIs.
Implementation of Azure or Aws Cloud Data Models & Services.
Knowledge of security standards, B2E, B2B & B2C security models.
On-premises to Cloud migration.
Solution Design of Data & Analytics systems on Cloud Services.
Knowledge on building Data Science ML models.

Bachelor’s or master’s degree in computer science or related engineering discipline.
Minimum 5 years of relevant experience with software design, architecture and development life cycle.
Minimum 3 years of significant experience with working on cloud, data analytics-based technologies on cross functional systems, API’s and integration frameworks (including micro services).
Hands on experience using Lambda, Step functions and other cloud services/API’s from either, AWS, MS Azure, Google cloud, MuleSoft, or SFDC, Webhooks or other related technologies.
Good written and verbal communication skills.
Ability to understand the big picture and come up with platform design/recommendation to stitch the same with defining/implementing standards for DevOps and best in class architectural principles.