Databricks Test Automation Engineer

Data & Databricks Test Automation Engineer

Company Overview

Citco is a global leader in financial services, delivering innovative solutions to some of the world's largest institutional clients. We are seeking a Test Automation Engineer specializing in Databricks and data platforms to ensure the quality and reliability of our data solutions.

Role Description

As a Data & Databricks Test Automation Engineer, you will be responsible for developing and implementing automated testing frameworks for Databricks-based solutions, data pipelines, and data quality validation. You will work closely with data engineering teams to ensure data accuracy and reliability across our Lakehouse architecture.

Key Responsibilities

1. Databricks Testing

• Design and implement automated testing for Databricks notebooks and workflows
• Create test frameworks for Delta Lake tables and ACID transactions
• Develop automated validation for structured streaming pipelines
• Validate Delta Live Tables implementations

2. Data Pipeline Testing

• Automate testing for ETL/ELT processes in Databricks
• Implement Spark job testing and optimization validation
• Create test cases for data ingestion and processing workflows
• Develop automated checks for data transformations
• Test Unity Catalog features and access controls

3. Quality Assurance

• Design and execute data quality test strategies
• Implement automated data reconciliation processes
• Develop performance testing for large-scale Spark jobs

4. Monitoring & Reporting

• Implement pipeline monitoring test frameworks
• Create automated test dashboards
• Generate quality metrics and testing reports
• Maintain comprehensive test documentation

Requirements & Qualifications

1. Educational Background

• Bachelor’s degree in Computer Science, Data Science, or related field
• Relevant certifications in Databricks or data testing are a plus

2. Technical Experience

• 2+ years hands-on experience with Databricks (Spark)
• Strong programming skills in Python (PySpark) and SQL
• Experience with data testing frameworks and tools
• Knowledge of AWS services (S3, Glue, Lambda)
• Understanding of Delta Lake and Lakehouse architecture
• Experience with version control systems (Git)

3. Additional Skills

• Strong analytical and problem-solving abilities
• Experience with large-scale data processing
• Knowledge of data quality best practices
• Understanding of data governance and compliance requirements
• Experience with Agile methodologies

4. Platform Knowledge

• Databricks workspace and notebook development
• Delta Lake and Delta Live Tables
• Unity Catalog for governance testing
• Spark optimization and performance testing