Lead Software Engineer - Data Engineering

Team Leadership & Management

• Lead, mentor, and manage a team of data engineers and platform developers.
• Foster a culture of technical excellence, collaboration, and continuous learning.
• Drive Agile practices and ensure timely delivery of high-quality solutions.

Technical Strategy & Architecture

• Architect and oversee the development of scalable, secure, and resilient data platforms.
• Design and implement near real-time data movement and streaming architectures using tools like Kafka, Spark, and cloud-native services.
• Establish best practices in data modelling, ETL/ELT, data governance, and metadata management.

Data Engineering & Snowflake Expertise

• Lead the development of robust data pipelines for ingestion, transformation, and delivery using Snowflake, dbt, and cloud-native tools.
• Optimize data storage, retrieval, and processing for performance, reliability, and cost-efficiency.
• Implement data quality frameworks, lineage tracking, and schema evolution strategies.

Big Data & Data Warehousing

• Build and maintain large-scale data lakes and data warehouses for structured and unstructured data.
• Design scalable data architectures to support manufacturing analytics, predictive maintenance, and supply chain optimization.

Cloud & Platform Engineering

• Leverage Azure and AWS services for data ingestion, transformation, and analytics.
• Deploy software using CI/CD tools (Azure DevOps preferred, Jenkins, AWS CloudFormation).
• Ensure platform scalability, security, and operational readiness across global deployments.

AI & Advanced Analytics Enablement

• Collaborate with Data Science and AI teams to operationalize ML models and analytics workflows.
• Promote integration of AI capabilities into data engineering pipelines (e.g., GenAI, MCP, ATA).
• Support real-time analytics and edge AI use cases in manufacturing environments.

Stakeholder Engagement

• Partner with product managers, manufacturing SMEs, and business leaders to understand requirements and deliver impactful data solutions.
• Communicate technical concepts to non-technical audiences and influence strategic decisions.

Must-Have Skills

• Proven experience in Big Data processing and Data Warehousing.
• Expertise in building end-to-end near real-time data pipelines for OLTP & OLAP.
• Strong architecture exposure for building robust, scalable Data Platforms.
• Deep expertise in Snowflake, SQL, NoSQL, and distributed data systems.
• Experience with data transformation tools (dbt, Apache Spark, Azure Data Factory).
• Strong analytical skills and solid knowledge of computer science fundamentals.
• Deep exposure to Azure and AWS cloud platforms.
• Good understanding of AI concepts and latest developments (Gen AI, MCP, ATA, etc.).

Nice-to-Have Skills

• Knowledge of the NVIDIA ecosystem and its applications in data and AI.
• Experience building production-ready AI solutions and integrating with MLOps workflows.
  • Familiarity with modern data visualization and BI tools (e.g., Power BI, Tableau, Looker).