Senior Data Engineer with Exp in Snowflake & Amazon QuickSight in India at Jobgether
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Job Description
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Data Engineer with Exp in Snowflake & Amazon QuickSight in India.
In this role, you will join a high-impact data engineering team focused on building scalable, reliable, and high-performance data platforms that power advanced analytics and business decision-making. You will work at the intersection of data engineering, cloud infrastructure, and analytics enablement, designing pipelines and data models that support enterprise-scale reporting and insights. The environment is fast-paced, collaborative, and centered on innovation, with strong exposure to modern cloud technologies and data stack practices. You will play a key role in transforming raw data into trusted, actionable datasets used across multiple business functions. This position offers the opportunity to work on complex data challenges involving Snowflake, AWS, and modern transformation frameworks. You will collaborate closely with analytics, product, and engineering teams to ensure data reliability and usability. The role is ideal for someone who enjoys solving technical problems while building systems that directly influence business outcomes.
You will be responsible for designing and maintaining scalable data pipelines and analytics-ready datasets that support enterprise reporting and decision-making, while ensuring performance, reliability, and data quality across systems.
- Design, develop, and optimize ETL/ELT pipelines for large-scale data platforms using modern cloud and data engineering tools
- Build and maintain data solutions using Snowflake, Python, and AWS services such as S3, Glue, and Lambda
- Develop and optimize advanced SQL queries, including CTEs, window functions, and performance tuning techniques
- Work with Snowflake components such as warehouses, streams, and tasks to ensure efficient data processing and orchestration
- Develop and maintain data transformation workflows using dbt to ensure structured and reusable data models
- Build reporting datasets and support dashboarding solutions using Amazon QuickSight
- Perform data validation, integrity checks, and root cause analysis to ensure accuracy and consistency
- Integrate and manage data across multiple systems including DynamoDB, S3, and other analytical platforms
- Monitor pipeline performance and troubleshoot production issues in collaboration with cross-functional teams
You bring strong hands-on experience in modern data engineering, with deep expertise in cloud-based data platforms, SQL optimization, and end-to-end pipeline development, along with the ability to collaborate effectively in a fast-paced environment.
- 5+ years of experience in data engineering or similar roles focused on building production-grade data systems
- Strong expertise in SQL, including CTEs, window functions, query optimization, and performance tuning
- Hands-on experience with Snowflake, including warehouses, streams, tasks, and data loading strategies
- Strong programming skills in Python for data processing and pipeline development
- Experience with AWS services such as S3, Glue, and Lambda in data engineering workflows
- Good understanding of dbt for building modular and maintainable data transformations
- Experience creating dashboards and reports using Amazon QuickSight
- Familiarity with DynamoDB, NoSQL databases, and distributed data systems
- Exposure to additional tools such as Rockset and basic to intermediate JavaScript is a plus
- Strong analytical thinking, problem-solving ability, and attention to data quality
- Excellent collaboration and communication skills to work across technical and business teams
- Competitive compensation aligned with experience and market standards
- Flexible remote or hybrid work arrangements depending on project needs
- Opportunity to work on modern cloud-native data platforms and large-scale analytics systems
- Exposure to cutting-edge technologies including Snowflake, AWS, and advanced BI tools
- Learning and development opportunities in data engineering and cloud architecture
- Collaborative and innovation-driven work environment
- Access to challenging, high-impact projects across global teams