DGM - Data Science

Key Responsibilities:

1) Data Architecture: a. Design and Implement Data Platforms and Infrastructure with considerations around Data storage strategy, Security, Latency, Reliability, Scalability and costs. b. Provide though leadership on the Data Management and Data Governance for the organization from a Data Architecture perspective ( data granularity, cross application data access design) c. Design and build an Enterprise Data Architecture and ensure that new applications built follow the EDA and that they conform to existing Data Models ( Logical/Physical)

2) Data Modeling and Warehousing : a. Create Relational and NoSQL data models to fit the needs of a diverse set of data consumers ( Data Analysts, Data Scientists and Business Analysts). b. Design and Build databases hosting a variety of enterprise data, both on-prem and Cloud, with robust design principles around Availability, Consistency and Performance c. Design and Implement Data Lakes for Analytics and AI/ML use cases

3) Data Access: a. Design and Build Database query infrastructure for custom Machine Learning applications including online and API based queries b. Design APIs to support Data requirements for Business Intelligence dashboards

4) Data Pipelines: a. Design and Implement ETL pipelines to ingest data into databases from Transactional systems, streaming sensor data, data files etc., b. Design and Implement automated schedules for monitoring data pipelines, data quality and data lineage.

5) MLOps/DevOps a. Design and implement the machine learning lifecycle at scale, from building the data infrastructure to train/test Machine learning models to their production environments. b. Management of production ML workflows ensuring automated CI/CD capabilities are built into the work flow c. Design and Implement alerts/dashboards to ensure continuous monitoring of production models’ effectiveness ( accuracy, latency, performance etc.,)

Job Requirements:

1) Ability Work closely with Data Analysts, Data Scientists, Business Analysts and Business stakeholders

2) Comfortable to work in cross-functional team and collaborate with peers during the project lifecycle

3) Open to travel based on the project and teams locations.

Qualifications:

1. BE/B.Tech/BS/MS/PhD in Computer Science or a related field from a Premier institute

2. Strong Preference to candidates with Cloud certifications (Azure)

Experience:

1) Minimum 10 years of work experience in Data Engineering with at least 3-4 years designing data platforms for enterprise-grade applications/ML use cases

2) Start-up experience is a plus