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Senior Data Engineer( DataBricks & Snowflake) at Andishi
Andishi
October 14, 2026
Full-time
On-site
We're looking for a skilled Data Engineer with strong Databricks administration experience to help build, manage, and improve cloud-based data solutions.
The project involves maintaining Databricks environments, developing scalable data pipelines, integrating data platforms, and improving overall data processing performance and reliability.
We need someone who is comfortable owning technical deliverables from start to finish, making sound engineering decisions, and solving problems independently.
What You'll Be Working On
Managing and optimizing Databricks workspaces, configurations, permissions, and performance.
Developing and maintaining reliable ETL/ELT workflows and data processing pipelines.
Working with Snowflake to support data integration, transformation, and storage.
Designing scalable data architectures for efficient processing and analytics.
Handling data migrations between platforms while maintaining data integrity.
Identifying and resolving pipeline failures, performance issues, and data quality problems.
Improving automation, monitoring, and operational efficiency.
Testing solutions, documenting implementations, and delivering production-ready work.
Technical Requirements
Must Have:
Strong hands-on Databricks administration experience
Python and advanced SQL
Apache Spark / PySpark
Snowflake
Data engineering and ETL/ELT development
Data migration and pipeline optimization
Experience with AWS, Azure, or GCP
Troubleshooting and performance tuning
Nice to Have:
Apache Airflow or Kafka
Terraform and CI/CD
Docker or Kubernetes
Scala
Data governance and access control
Cloud infrastructure automation
Expected Deliverables
Configured and optimized Databricks environments
Functional and tested data pipelines
Reliable integrations with required data platforms
Completed data migration tasks with validation
Resolved performance and reliability issues
Documented architecture, configurations, and workflows
Source code, test results, and deployment instructions
Final technical handover
Who We're Looking For
You should have at least 4 years of relevant experience and a strong background in production data engineering.
We're especially interested in developers who have worked with complex data environments, can troubleshoot independently, and understand how to build maintainable, high-performance solutions.
You should be comfortable working remotely, communicating progress clearly, and delivering agreed milestones without constant supervision.
The project involves maintaining Databricks environments, developing scalable data pipelines, integrating data platforms, and improving overall data processing performance and reliability.
We need someone who is comfortable owning technical deliverables from start to finish, making sound engineering decisions, and solving problems independently.
What You'll Be Working On
Managing and optimizing Databricks workspaces, configurations, permissions, and performance.
Developing and maintaining reliable ETL/ELT workflows and data processing pipelines.
Working with Snowflake to support data integration, transformation, and storage.
Designing scalable data architectures for efficient processing and analytics.
Handling data migrations between platforms while maintaining data integrity.
Identifying and resolving pipeline failures, performance issues, and data quality problems.
Improving automation, monitoring, and operational efficiency.
Testing solutions, documenting implementations, and delivering production-ready work.
Technical Requirements
Must Have:
Strong hands-on Databricks administration experience
Python and advanced SQL
Apache Spark / PySpark
Snowflake
Data engineering and ETL/ELT development
Data migration and pipeline optimization
Experience with AWS, Azure, or GCP
Troubleshooting and performance tuning
Nice to Have:
Apache Airflow or Kafka
Terraform and CI/CD
Docker or Kubernetes
Scala
Data governance and access control
Cloud infrastructure automation
Expected Deliverables
Configured and optimized Databricks environments
Functional and tested data pipelines
Reliable integrations with required data platforms
Completed data migration tasks with validation
Resolved performance and reliability issues
Documented architecture, configurations, and workflows
Source code, test results, and deployment instructions
Final technical handover
Who We're Looking For
You should have at least 4 years of relevant experience and a strong background in production data engineering.
We're especially interested in developers who have worked with complex data environments, can troubleshoot independently, and understand how to build maintainable, high-performance solutions.
You should be comfortable working remotely, communicating progress clearly, and delivering agreed milestones without constant supervision.