Senior Data Engineer

Job Title

Experience

Location

Required Skills & Experience

• 10+ years of hands-on experience in Data Engineering, including the design, development, and support of complex data ecosystems.
• Proven track record in enterprise data warehouse (EDW) design, implementation, and optimization.
• Strong command of data modeling techniques (relational, dimensional) to ensure efficient storage and retrieval.
  

• Deep experience with Snowflake, including performance tuning, query optimization, and leveraging native features like Snowpipe, Streams, and Tasks.
  

• Expertise in ETL/ELT processes and tools.
• Hands-on experience with Matillion, Fivetran, and HVR for pipeline development.
• Skilled in integrating data from diverse sources via APIs, EDI, SFTP, etc.
  

• Ability to translate business requirements into scalable and efficient data models.
• Familiarity with best practices in schema design and normalization.
  

• Experience implementing data validation, quality checks, and governance frameworks.
• Knowledge of data security, access control, and privacy regulations (e.g., GDPR).
  

• Proficient in integration testing for data pipelines and EDWs.
• Capable of designing robust error handling and recovery mechanisms.
  

• Strong interpersonal skills to work with cross-functional teams (data scientists, analysts, business stakeholders).
• Excellent verbal and written communication to explain technical concepts to non-technical audiences.
  

• Experience working in Agile/Scrum environments.
  

• Proven ability to maintain data accuracy and consistency across multiple systems.
  

• Experience across the full lifecycle of BI/EDW implementations: blueprinting, build/test, go-live, and support.
  

Preferred Skills

• Experience with external partner integrations (eCommerce, EDI, WMS, B2B).
• Familiarity with Snowflake Marketplace.
• Proficiency in SQL, Python, and Bash.
• Exposure to Power BI or other visualization tools.
• Cloud experience with AWS, Azure, or Google Cloud.
• Understanding of containerization (Docker, Kubernetes).
  

Key Responsibilities

• Design and maintain scalable data pipelines for ETL/ELT processes.
• Build and manage data models within the EDW for analytics and reporting.
• Translate business requirements into technical specifications.
• Integrate data from internal systems and external partners.
• Develop dashboards and reports using Power BI.
• Conduct integration testing and ensure data quality.
• Implement and maintain data security and access controls.
• Collaborate with stakeholders to align data solutions with business needs.
• Support production environments and troubleshoot data issues.
• Participate in cutover planning and execution.
• Stay current with industry trends and emerging technologies.