Snowflake Data Engineer

Job Summary

Wissen Technology is hiring an experienced Senior Data Engineer to design, build, and maintain enterprise-grade data platforms and modern cloud data warehouses. The role focuses on product development, data pipeline engineering, analytics enablement, and ongoing platform optimization using Snowflake, AWS Glue, Python, and AWS services.

Experience

7-12 years

Mandatory Skills (Must Have)

• Snowflake (7+ years including data modeling, performance tuning, security roles, and warehouse optimization)
• Python (7+ years for ETL/ELT development, automation, and data processing)
• AWS Glue (Glue Jobs, Crawlers, Data Catalog, and serverless ETL development)
• ETL/ELT pipeline design and development in enterprise data environments
• AWS services including S3, Lambda, IAM, and cloud-native data architecture
• Data warehousing concepts, dimensional modeling, and analytics data marts
• SQL and advanced data transformation techniques for large-scale datasets

Optional Skills (Good to Have)

• Healthcare data analytics and specialty pharmacy data experience
• Apache Airflow or AWS Step Functions for workflow orchestration
• CI/CD pipelines using Git, Jenkins, GitHub Actions, or similar tools
• Data quality, observability, and monitoring platforms
• Infrastructure as Code and cloud automation practices

Professional Attributes & Qualifications

• Education: BE/BTech/ME/MTech in Computer Science, Engineering, Information Technology, or related field
• Leadership: Experience mentoring junior data engineers and guiding technical best practices
• Ownership: Proven ability to drive end-to-end data engineering projects independently
• Strong analytical, problem-solving, and stakeholder management skills
• Excellent written and verbal communication skills for business and technical audiences

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Snowflake, AWS Glue, and Python
• Build robust Snowflake data models and warehouse structures supporting analytics, reporting, and data science initiatives
• Develop clean, efficient, and maintainable Python code for data processing and automation
• Collaborate with data analysts, data scientists, architects, and business stakeholders to deliver high-quality data solutions
• Gather requirements, provide solution design recommendations, and communicate technical approaches effectively
• Monitor, troubleshoot, and optimize data workflows for reliability, performance, and data quality
• Implement data validation, error handling, observability, and governance controls across pipelines
• Optimize cloud data platform performance and cost efficiency in AWS environments