This is a remote position.
We are looking for an experienced Data Engineer with strong hands-on experience in Azure Data Factory (ADF), Snowflake, dbt, and SQL. The ideal candidate will be responsible for building and maintaining scalable data pipelines, transforming data, and developing reliable data solutions for analytics and reporting.
- Design, develop, and maintain ETL/ELT data pipelines using Azure Data Factory (ADF).
- Build and optimize data solutions using Snowflake as the cloud data warehouse.
- Develop data transformation models using dbt (Data Build Tool).
- Write complex and optimized SQL queries, stored procedures, views, and transformations.
- Develop data pipelines to ingest data from various sources including APIs, databases, files, and enterprise applications.
- Perform data cleansing, transformation, validation, and reconciliation to ensure data quality and accuracy.
- Implement incremental data loads, scheduling, dependency management, and error handling in ADF.
- Develop scalable and optimized Snowflake data models, tables, views, and SQL transformations.
- Build and maintain dbt models, tests, macros, and documentation.
- Troubleshoot pipeline failures, data issues, and performance problems across ADF, Snowflake, and dbt.
- Work with business analysts, data architects, and other engineering teams to understand data requirements and deliver solutions.
- Support production deployments, monitoring, and ongoing enhancement of data pipelines.
- 4+ years of experience in Data Engineering.
- Strong hands-on experience with:
- Azure Data Factory (ADF)
- Snowflake
- dbt
- Advanced SQL
- Azure Data Factory (ADF)
- Strong understanding of ETL/ELT concepts and data warehousing.
- Experience developing complex data pipelines and data transformations.
- Good understanding of dimensional data modeling, including fact and dimension tables.
- Experience with Snowflake performance optimization and query tuning.
- Hands-on experience with dbt models, tests, incremental models, macros, and Jinja.
- Strong troubleshooting and production support skills.
- Experience with Azure cloud services, particularly Azure Storage, Azure Functions, Databricks, or Key Vault.
- Experience integrating data through REST APIs, JSON, CSV, and relational databases.
- Experience with Python or PySpark is a plus.
- Experience with Git and CI/CD using Azure DevOps or similar tools.
- Understanding of data governance, data quality, and security best practices.
- Experience working with large-scale enterprise data platforms.
Skills Required
- 4+ years of experience in data engineering
- Hands-on experience with Azure Data Factory
- Hands-on experience with Snowflake
- Hands-on experience with dbt
- Advanced SQL experience
- Strong understanding of ETL/ELT concepts and data warehousing
- Experience developing complex data pipelines and data transformations
- Understanding of dimensional data modeling, including fact and dimension tables
- Experience with Snowflake performance optimization and query tuning
- Experience with dbt models, tests, incremental models, macros, and Jinja
- Strong troubleshooting and production support skills
- Experience with Azure cloud services, particularly Azure Storage, Azure Functions, Databricks, or Key Vault
- Experience integrating data through REST APIs, JSON, CSV, and relational databases
- Experience with Python or PySpark
- Experience with Git and CI/CD using Azure DevOps or similar tools
- Understanding of data governance, data quality, and security best practices
- Experience working with large-scale enterprise data platforms
What We Do
Everest Technologies is an enterprise IT services firm that helps organizations solve business problems and scale through technology. Its offerings include managed services, project solutions, staff augmentation, DevOps and automation, quality engineering, cloud enablement, application services, retail and supply-chain technology, and decision intelligence. The company combines domain expertise with software engineering and AI capabilities, serving enterprise clients globally from U.S. and Indian delivery centers.






