Description

Key Skills: Python, Snowflake, SQL, Data Engineering, Data Modeling, ETL, Cloud Data Platforms, Performance Optimization, Version Control, Agile

Good to Have Skills: Experience with Snowflake Cortex, Snowpipe, industrial manufacturing analytics, dimensional modeling, automated testing frameworks, shop floor systems, production planning, quality management, asset maintenance data, collaboration tools for hybrid work environments.

Roles & Responsibilities:

• Design and implement robust Snowflake data models that support complex industrial manufacturing analytics and reporting needs while ensuring scalability and performance tuning across all environments.
• Develop schedule and monitor Snowflake tasks that orchestrate critical data workflows to ensure timely and accurate data availability for operations planning and financial stakeholders.
• Configure and maintain Snowflake streams to capture change data from key manufacturing systems enabling near real time insights into production performance and quality metrics.
• Build and optimize Snowpipe based ingestion pipelines that load diverse industrial data sources into Snowflake with high reliability resilience and minimal latency.
• Create efficient and maintainable Snowflake SQL code including views stored procedures and analytic queries that drive standardized metrics and dashboards for plant and enterprise users.
• Develop modular and reusable Python components that integrate with Snowflake Cortex to support advanced analytics predictive modeling and optimization use cases in industrial manufacturing.
• Collaborate with product owners process engineers and data analysts to translate manufacturing requirements into technical designs that align with data architecture standards and governance policies.
• Implement rigorous data quality checks and validation routines in Python and Snowflake to ensure accuracy completeness and consistency of production inventory and maintenance data.
• Optimize query performance and warehouse configurations in Snowflake to balance cost efficiency with fast response times for critical manufacturing and supply chain analytics workloads.
• Document end to end data flows technical designs coding standards and operational runbooks to support maintainability and knowledge sharing across the global development team.
• Provide technical guidance to peers on Python best practices Snowflake features and industrial data patterns while fostering a culture of continuous improvement in data engineering.
• Coordinate with enterprise security and compliance teams to apply proper access controls data masking and audit capabilities within Snowflake environments that handle sensitive manufacturing information.
• Participate in agile ceremonies and sprint planning to estimate effort manage priorities and deliver high quality data solutions on time within a hybrid work model.

Experience Required: 6 to 9 years of extensive hands-on experience in Python development focused on data engineering automation and integration with modern cloud data platforms

Key Skills

Education

Any Graduate