Snowflake/ Databricks Data Engineer | About YouAs a Snowflake/ Databricks Data Engineer, you are responsible for transforming raw data into trusted, authoritative sources that drive business decisions. You thrive in a fast-paced, agile environment and enjoy solving complex data integration challenges. You're passionate about data commercialization, AI-driven insights, and enabling self-service analytics across the organization. Your ability to collaborate across teams and leverage modern cloud technologies like Azure and Snowflake makes you a key player in our data strategy.
Snowflake/ Databricks Data Engineer | Day-to-Day - Design and maintain scalable data pipelines using Snowflake or Databricks, Azure, and Azure Service Bus to support enterprise-wide initiatives.
- Lead data integration efforts, extracting data from external sources and landing it in Snowflake, including data modeling and transformation.
- Collaborate with stakeholders to develop authoritative data sources that support data commercialization and strategic decision-making.
- Use Agile tools like Jira, ServiceNow, and Azure DevOps for sprint planning, backlog grooming, and daily stand-ups.
- Support modernization efforts by transitioning from legacy tools (e.g., SnowMirror) to cloud-native solutions.
- Enable self-service analytics through platforms like Power BI and Sigma, ensuring data integrity and accessibility.
Snowflake/ Databricks Data Engineer | Skills & Experience - 5+ years of experience in data engineering, data architecture, or a related technical field.
- Strong hands-on experience with Snowflake, Databricks, Azure, and Azure Service Bus in enterprise environments.
- Proven ability in data modeling, pipeline development, and scalable data architecture.
- Familiarity with Agile methodologies and tools such as Jira, ServiceNow, and Azure DevOps.
- Working knowledge of Power BI, Sigma, and principles of self-service analytics.
- Exposure to Python and interest in collaborating on automation, scripting, and AI-driven data initiatives.
