AWS Data Engineer 12+ years

Role – Senior Data Engineer

Location – Remote – 12+ years (Those who are completed project / going to end will work)

 

Skills – AWS, Snowflake, DBT, PySpark, CI/CD, Data Model, SQL

 

Job Description:

         We are looking for an experienced Senior Data Engineer (12+ years of data engineering experience) to join the EDH team. This role will serve as a technical resource responsible for designing, developing, supporting, and enhancing modern data pipelines built using AWS, Snowflake, and DBT.

The ideal candidate should have strong hands-on experience building enterprise-scale data platforms, working with AWS, Snowflake cloud-based data engineering solutions, and supporting complex data integration and transformation processes. The candidate should be comfortable working independently, collaborating with offshore teams, and providing technical guidance.

Key Responsibilities:

• Design, develop, and support enterprise data pipelines using AWS, Snowflake, and DBT.
• Develop and enhance metadata-driven data ingestion and transformation frameworks.
• Work with AWS services to build scalable data ingestion solutions.
• Implement enterprise-scale solutions using Snowflake, including database design, data loading, data transformation, security, performance optimization, and operational support.
• Build dimensional models, star schema, snowflake schema, fact and dimension tables, and data structures optimized for analytics and reporting.
• Develop DBT models, macros, tests, and deployment configurations.
• Troubleshoot and debug data pipeline issues across AWS, Snowflake, dbt, and PySpark, perform root cause analysis, and implement solutions.
• Support EDH production deployments, monitoring, and issue resolution.
• Collaborate with offshore engineering teams and provide technical guidance and code reviews.
• Participate in architecture discussions and recommend improvements to platform design.
• Work with DevOps teams on CI/CD processes, Git-based development, deployment automation, and release management.
• Implement data quality checks, validation frameworks, logging, and operational monitoring.

 

Required Technical Skills:

AWS: Strong hands-on data engineering experience with AWS data services

Snowflake: Strong hands-on experience with Snowflake architecture, development, Designing data warehouse solutions using Snowflake.

DBT: Strong hands-on experience with DBT development

PySpark: Experience developing PySpark applications for data ingestion and cleansing.

DevOps-CI/CD: Experience with deployment automation, release management, and environment promotion processes.

Data Modeling: Experience designing dimensional data models (Facts, Dimensions).

 transformation, and optimization in cloud-based data platforms.

SQL: Strong SQL skills including complex queries, performance tuning, and optimization.

Thanks

Yogesh Sharma K,

Reveille Technologies, Inc

yogesh@reveilletechnologies.com