IT - Data Engineer - Expert Level

Job Summary: Expert Data Analytics Engineer (Data Engineer - Expert Level), Join a forward-thinking team as an Expert Data Analytics Engineer and architect the next generation of enterprise analytics. Lead the design and optimization of complex data models using DBT and Snowflake, setting the standard for data-driven decision-making across the organization. This role offers the chance to shape analytics engineering best practices, collaborate with diverse technical teams, and drive impactful enterprise initiatives., Architect and deliver advanced star-schema data models, including fact, dimension, bridge, and aggregate tables for scalable analytics.

• Build, optimize, and govern DBT frameworks, reusable models, and rigorous testing strategies.
• Design, optimize, and troubleshoot large-scale Snowflake data structures, data pipelines, and SQL workloads for performance and reliability.
• Set and enforce data modeling standards, best practices, and design patterns for the analytics ecosystem.
• Partner cross-functionally with Data Engineers, BI Developers, Product Owners, Architects, and stakeholders to deliver high-impact solutions.
• Mentor and lead teams, conduct technical reviews, and provide architectural guidance across analytics engineering projects.
• Champion data quality, performance, governance, documentation, and continuous platform improvement.

Extensive hands-on expertise with DBT development, testing, and deployment.

• Deep knowledge of Snowflake architecture, performance tuning, and SQL optimization.
• Proven background in designing and implementing enterprise dimensional data models.
• Strong grasp of data warehousing, analytical modeling, and modern analytics engineering principles.
• Demonstrated leadership in technical design and influencing data architecture decisions.
• Excellent communication skills, with the ability to translate complex technical concepts into business value.

Preferred Skills

• Experience with Azure Data Factory (ADF), Synapse, or Microsoft Fabric.
• Proficiency in Python for data engineering and automation.
• Familiarity with Data Vault or advanced data modeling methodologies.
• Relevant certifications such as DP-203 or SnowPro.

Lead the analytics transformation of a large-scale enterprise environment.

• Collaborate with top-tier technical talent in a culture that values innovation and continuous learning.
• Gain exposure to cutting-edge data engineering tools and cloud technologies.
• Opportunity for career advancement in analytics architecture and engineering leadership.