Lead the data architecture and engineering strategy, ensuring alignment with business and technology roadmaps
Design and implement data models, pipelines, and data integration frameworks across multiple platforms
Partner with stakeholders to translate business requirements into scalable data solutions
Optimize data pipelines for performance, scalability, and reliability, including query tuning and resource management within Snowflake
Drive adoption of best practices in data engineering design patterns and modern cloud architectures
Implement and monitor data validation procedures to ensure data accuracy and consistency across systems
Work closely with project managers, data architects, and business analysts to align project milestones and deliverables with business goals
Mentor and guide data engineering teams (onsite & offshore) to deliver high-quality outcomes
Ensure compliance with data governance, security, and privacy standards
Create and maintain detailed documentation of data pipelines, data flow diagrams, and transformation logic
Troubleshoot and resolve issues related to data pipelines, including job failures and performance bottlenecks.
Requirements
Bachelor’s degree in Computer Science, Information Technology, or a related field
8+ years of experience in data engineering with a strong focus on Data Architecture, Data Modelling (Conceptual, Logical, Physical), ELT processes and data pipeline development
Hands-on experience with Snowflake cloud data platform, including data sharing, secure views, and performance optimization
Proficiency in SQL and familiarity with data integration and ETL/ELT tools
AWS Technologies (Glue, EMR)
Python for data engineering workflows
Strong understanding of data engineering design patterns
Strong problem-solving skills and the ability to work independently to meet deadlines
Excellent communication skills for effectively interacting with technical and non-technical stakeholders.
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