Senior Snowflake Data Engineer:

Wissen Technology is hiring for Senior Data Engineer (Snowflake & AWS Glue)

ABOUT WISSEN TECHNOLOGY

At Wissen Technology, we deliver niche, custom-built products that solve complex business challenges across industries worldwide. Founded in 2015, our core philosophy is built around a strong product engineering mindset—ensuring every solution is architected and delivered right the first time. Today, Wissen Technology has a global footprint with 2000+ employees across offices in the US, UK, UAE, India, and Australia. Our commitment to excellence translates into delivering 2X impact compared to traditional service providers. How do we achieve this? Through a combination of deep domain knowledge, cutting-edge technology expertise, and a relentless focus on quality. We don't just meet expectations—we exceed them by ensuring faster time-to-market, reduced rework, and greater alignment with client objectives. We have a proven track record of building mission-critical systems across industries, including financial services, healthcare, retail, manufacturing, and more. Wissen stands apart through its unique delivery models. Our outcome-based projects ensure predictable costs and timelines, while our agile pods provide clients the flexibility to adapt to their evolving business needs. Wissen leverages its thought leadership and technology prowess to drive superior business outcomes. Our success is powered by top-tier talent. Our mission is clear: to be the partner of choice for building world-class custom products that deliver exceptional impact—the first time, every time.

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, LOCATION, MODE OF WORK

Experience: 7-12 years

Location: Chennai

Mode of Work: Hybrid

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

Wissen Sites

• Website: www.wissen.com

• LinkedIn: https://www.linkedin.com/company/wissen-technology

• Wissen Leadership: https://www.wissen.com/company/leadership-team/

• Wissen Live: https://www.linkedin.com/company/wissen-technology/posts/feedView=All

• Wissen Thought Leadership: https://www.wissen.com/articles/