Role – Senior Data Engineer
Location ā Remote ā 12+ years
Skills ā AWS, Snowflake, DBT, PySpark, CI/CD, Data Model, SQL (AWS, Snowflake, Pyspark, DBT ā Must)
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.
