Principal Data Engineer (oog) Job in Tvs Motors

We are looking to welcome someone who joins us an Principal Data Engineer for OOG (Order Obtainment Group). OOG group includes customer facing & commercial functions like Market research, Marketing, Sales, Distribution channel management, Digital Assets development (website & Apps), Spare Parts & services business and Customer experience, for both domestic and international businesses of TVSM.

Someone with solid architecting, development & deployment experience in data engineering, DevOps, scalable machine learning model & API development. Someone who believes in product thinking and data-as-a-service principles. Someone who is a servant leader to promising engineers, someone who empowers his/her colleagues towards achieve greater goals on their own.

Our Data engineering team is responsible for the data architecture, warehousing and data processing pipelines that power various web & mobile applications, our analytics products and services, and feed our machine learning solutions.

What will you learn and do?

Data Architecture:

Design and Implement Data Platforms and Infrastructure with considerations around Data storage strategy, Security, Latency, Reliability, Scalability and costs.

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)

Data Modelling and Warehousing :

Create Relational and NoSQL data models to fit the needs of a diverse set of data consumers ( Data Analysts, Data Scientists and Business Analysts).

Design and Build databases hosting a variety of enterprise data, both on-prem and Cloud, with robust design principles around Availability, Consistency and Performance

Design and Implement Data Lakes for Analytics and AI/ML use cases

Data Access:

Design and Build Database query infrastructure for custom Machine Learning applications including online and API based queries

Design APIs to support Data requirements for Business Intelligence dashboards

Data Pipelines:

Design and Implement ETL pipelines to ingest data into databases from Transactional systems, streaming sensor data, data files etc.,

Design and Implement automated schedules for monitoring data pipelines, data quality and data lineage.

MLOps/DevOps

Design and implement the machine learning lifecycle at scale, from building the data infrastructure to train/test Machine learning models to their production environments.

Management of production ML workflows ensuring automated CI/CD capabilities are built into the work flow

Design and Implement alerts/dashboards to ensure continuous monitoring of production models effectiveness ( accuracy, latency, performance etc.,)

Your responsibilities

• Cultivate a customer-centric, results-driven data engineering organization
• Partner with internal teams and external vendors to ingest, store and enrich data throughout the organization within the enterprise data lake and underlying warehouses/data marts/etc
• Operate as a thought leader with the ability to guide, influence, and inspire peak performance across the data architecture design and ETL functions
• Lead large-scale integration and replatforming efforts with CRM and Customer Engagement Platform (CEP) systems both internally and externally to enhance the data and marketing platform infrastructure
• Collaborate with Business leaders, Data Science, IT and Digital App Development teams on implementing machine learning algorithms at scale to facilitate audience intelligence, segmentation and personalization initiatives
• Collaborate with Business Intelligence and extended analytics groups on data mart optimizations, query tuning, and data model designs with a focus on delivering actionable insights
• Work strategically to align data assets, storage, and computation/query layers to support long-term data platform goals, help define data models, publish metadata, guide best practice ETL standards
• Make sound architectural decisions across relational, multi-dimensional, distributed and object-based storage platforms
• Mentor junior engineers and participate in code reviews