Senior Data Engineer

Job Description:

The Senior Data Engineer will support the development, maintenance, optimization, and use of the Company’s data infrastructure. This role is looking for a collaborative, well-rounded professional with expertise in building scalable data solutions and enabling data-driven insights. As a key member of the growing data team, the Senior Data Engineer will have significant opportunities to shape the Company’s data platform, drive innovation, and support advanced analytics and AI/ML initiatives.

This role will require 3–5 years of experience in data engineering, with a strong preference for expertise in Snowflake. Experience with SQL Server, Azure-based cloud environments, and integrating data across custom in-house systems and third-party SaaS applications is highly valued.

Primary Responsibilities:

• Data Architecture and Modeling: Design, build, and maintain scalable data models, pipelines, and integrations to ensure data reliability and availability.
• Data Pipeline Development: Develop, optimize, and automate pipelines in Snowflake on Azure; maintain and enhance existing SSIS-based ETL processes where needed.
• Data Warehouse Management: Manage and optimize Snowflake environments, ensuring performance, scalability, and cost efficiency.
• Snowflake Advanced Capabilities: Leverage the full suite of Snowflake tools (e.g., semantic modeling, data sharing, Snowpark, and integration with AI/ML platforms) to support advanced analytics, predictive modeling, and enterprise reporting.
• Cloud & Infrastructure Support: Deploy, monitor, and maintain data systems in Azure, including integrations with Data Factory, Data Lake, and related services.
• Application Integration: Develop and maintain data flows across custom-built applications and SaaS platforms to ensure data consistency and usability.
• Data Governance & Quality: Establish and enforce standards for data quality, security, compliance, and lineage; support development and use of comprehensive semantic models.
• Cross-Team Collaboration: Partner with business stakeholders, analysts, and data scientists to deliver accessible, reliable data for decision-making.
• Innovation & Best Practices: Research and recommend adoption of emerging tools (e.g., dbt, Airflow) to strengthen our data ecosystem.

Qualifications:

• 5+ years of experience in data engineering or a closely related field.
• Expertise with Snowflake (design, development, and performance optimization).
• Expertise in data modeling, governance, and quality best practices.
• Hands-on experience with Azure services (Data Factory, Data Lake, Synapse, etc.).
• Advanced proficiency in SQL, Python, and Power BI.
• Familiarity with SQL Server/SSIS for developing and maintaining ETL processes.
• Experience integrating custom applications and third-party SaaS platforms into enterprise data environments.
• Excellent communication and collaboration skills across technical and business teams.