Data Engineer

Data Management, Data Warehousing, Analysis Skills, Cloud Computing, Snowflake Schema, Performance Tuning/Optimization, Cloud Architecture, Amazon Web Services (AWS), SQL (Structured Query Language), Oracle PL-SQL, * Minimum 7 years of experience in Data Management, with deep expertise in analytical data warehousing and enterprise-scale data platforms, leading complex data initiatives end to end.

• Minimum 3 years of hands-on experience with Snowflake Cloud Data Warehouse, including advanced features and performance optimization for large, concurrent analytics workloads.
• Strong expertise in AWS cloud architecture, with hands-on experience designing and supporting scalable, secure, and cost efficient data solutions using core AWS services.
• develop complex SQL and PL/SQL procedures to support robust, high performance data integration and transformation frameworks.
• Provide solutions using Snowflake services such as Snowpark, Streams, Tasks, and Snowpipe to build real time and batch data integration solutions in an AWS ecosystem.
• Knowledge in designing, building, and operating agentic AI systems within the Snowflake Data Cloud, leveraging Cortex AI capabilities
• Drive data architecture decisions by applying strong knowledge of logical and physical data models, enabling analytics, reporting, and business intelligence at scale.
• Lead the development of dimensional models, including slowly changing dimensions (SCDs) and various fact table designs, aligned with analytics and reporting best practices.
• Support unit testing, system integration testing, and UAT, and ensuring production ready data solutions.
• Expertise in SQL performance tuning, proactive monitoring, root cause analysis, and resolution of complex data pipeline and platform issues.
• Act as a developer within Agile delivery teams, contributing to sprint planning, story design, estimation, and documentation using Jira.
• Demonstrate strong verbal and written communication skills, effectively collaborating with architects, product owners, business stakeholders, and cross functional technology teams