Manager

Job Summary:

We are seeking a highly skilled and experienced Snowflake Data Engineer (Manager level) to lead data engineering initiatives using Snowflake and related technologies. The ideal candidate will possess strong hands-on experience in modern data platforms, cloud data warehouses and team leadership. You will be responsible for designing, implementing and optimizing scalable data solutions to support advanced analytics, reporting and business intelligence needs.

Key Responsibilities:

• Design and development of scalable data pipelines using Snowflake.
• Architect, implement and maintain data models, data marts and data pipelines across structured and semi-structured data sources.
• Collaborate with data scientists, business analysts and application teams to understand data requirements and deliver fit-for-purpose solutions.
• Implement data governance and security best practices, including role-based access control, data masking and audit logging.
• Develop and optimize ELT/ETL workflows using Snowflake SQL, dbt, ADF, or other orchestration tools.
• Monitor and improve performance and cost-efficiency of Snowflake compute and storage usage.
• Mentor junior engineers and provide technical oversight on projects and best practices.
• Stay current with evolving technologies in cloud data engineering and recommend innovations as appropriate.
• Collaborate with data scientists, analysts, and stakeholders to gather requirements and define data models that effectively support business requirements
• Demonstrate decision-making, analytical and problem-solving abilities
• Strong verbal and written communication skills to manage client discussions
• Familiar with working on Agile methodologies - daily scrum, sprint planning, backlog refinement

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.
• 8+ years of experience in data engineering or data warehousing, with at least 3+ years of hands-on experience with Snowflake.
• Strong experience in SQL, Python, and data pipeline development.
• Hands-on experience with cloud platforms (preferably Azure or AWS).
• Proficient in data modeling techniques, including star/snowflake schemas and slowly changing dimensions.
• Experience with data orchestration tools such as Apache Airflow, Azure Data Factory (ADF), or Informatica.
• Strong understanding of CI/CD, version control (Git), and DevOps practices in a data environment.

Preferred Skills:

• Experience with dbt (data build tool) for transformation logic.
• Knowledge of data cataloging, lineage, and governance frameworks.
• Exposure to BI tools like Power BI, Tableau, or Looker.
• Familiarity with Delta Lake, Databricks, or BigQuery is a plus.