Senior Data Engineer

Responsibilities

• Design, develop, and maintain scalable and reliable data pipelines to support analytics, reporting, and business decision-making.
• Extract, analyze, and manage existing Snowflake roles, grants, privileges, and related metadata.
• Design and implement a configuration-driven management framework using version-controlled files stored in Git.
• Ensure data security, integrity, and compliance during Snowflake role migration, with an initial focus on data roles automation.
• Build, optimize, and support ETL/ELT pipelines for structured and semi-structured data from multiple sources.
• Monitor, troubleshoot, and enhance production data pipelines for performance, reliability, and scalability.
• Implement and maintain Data Vault data models in Snowflake to support large-scale analytics and BI use cases.
• Write, optimize, and maintain high-performing SQL queries for data transformation and reporting.
• Collaborate closely with data architects, product managers, analysts, and data scientists to deliver impactful data solutions.
• Engage with business stakeholders to translate requirements into scalable technical solutions.
• Work with cloud platforms (AWS/Azure), DBT, and Snowflake to deliver cloud-native data solutions.

• 6–8 years of hands-on experience in data engineering roles.
• Advanced proficiency in Python for automation and data engineering workflows.
• Strong command of SQL for complex transformations and performance optimization.
• Experience with DBT for data transformation and modeling.
• Solid understanding of ETL/ELT architectures and pipeline orchestration.
• Hands-on experience with cloud platforms (AWS and/or Azure).
• Experience implementing Data Vault modeling in Snowflake.
• Familiarity with Docker and modern data engineering tooling.
• Exposure to PySpark and large-scale data processing frameworks.

• Design scalable, secure, and maintainable data architectures.
• Automate infrastructure and data workflows using Python and SQL.
• Translate business and analytical requirements into technical data solutions.

• Opportunity to work on cutting-edge data engineering solutions using modern cloud and analytics technologies.
• Exposure to large-scale retail data platforms supporting business-critical analytics.
• A collaborative, innovative environment that values technical excellence and continuous improvement.
• Opportunities for professional growth, skill enhancement, and technical leadership.

Want to discuss this opportunity in more detail? Feel free to reach out.