Description
Description
We are seeking a highly skilled DataBricks Tester to join our team. The ideal candidate will have strong expertise in ETL, Databricks, workflow orchestration, SQL, Python, Pyspark/Javaspark and Java scripting. The role requires someone capable of analyzing complex data logic, extracting business rules from code, designing and executing test strategies, and automating testing processes to ensure high-quality data solutions.
Key Responsibilities:
Analyze business and technical requirements, ensuring complete test coverage across data mapping, data pipelines, transformations, and reporting layers.
Review code conversion, logic extraction, and validation of complex transformation rules from source to target to identify test coverage
Develop, execute, and maintain test cases, test scripts, test data, and automation frameworks for ETL or Databricks pipelines, Databricks notebooks, and workflow orchestration jobs.
Validate data ingestion, transformation, aggregation, cleansing, and reporting logic against business requirements, code conversions, business logics/rules
Proficiency in validating flat files (CSV, TSV, TXT, fixed-length) including delimiter handling, header validation, null value handling, and schema verification.
Conduct data reconciliation between source, staging, and target systems to ensure accuracy and completeness.
Design and implement SQL- and Python-based automation frameworks for regression, smoke, and system integration testing.
Test data quality dimensions such as accuracy, completeness, consistency, timeliness, and validity.
Perform negative testing, boundary testing, and exception handling to ensure robustness of pipelines.
Collaborate with developers, data engineers, architects, and business analysts to identify data gaps, defects, and performance issues.
Conduct performance testing of queries and transformations to identify bottlenecks and recommend optimizations.
Provide clear and detailed defect reports, test execution results, and testing dashboards to stakeholders.
Support CI/CD integration of automated test scripts into deployment pipelines.
Participate in Agile ceremonies (stand-ups, sprint planning, retrospectives) and contribute to continuous improvement of test processes.
Mentor junior team members in best practices for data testing and automation.
Qualifications
Required Skills & Qualifications:
BS degree in related field (4 years of experience in lieu of degree)
Active IRS MBI Clearance
5+ years of experience in data engineering or data testing roles.
Proven experience with ETL testing and data validation in large-scale enterprise environments.
Strong in creating test cases, writing SQL/Python scripts to validate test cases for data manipulation, validations, Reports and Files validations, Comparisons Validation
Hands-on experience with Databricks (notebooks, workflow, clusters, pipelines, jobs, reports, delta lake).
Expertise in workflow orchestration tools such as Airflow, Azure Data Factory, or Control-M.
Advanced proficiency in SQL (complex joins, CTEs, window functions, query optimization, stored procedures).
Strong scripting skills in Python (pandas, PySpark, unittest/pytest) and Java/JavaScript for test automation framework in Selenium, TestNG, SOAPUI for backend API testing
Ability to interpret complex transformation logic and translate it into test validation rules.
Strong knowledge of data warehouse concepts, star/snowflake schemas, fact/dimension validation.
Experience testing structured and semi-structured data (JSON, XML, Parquet, Avro, CSV) and comparisons
Experience with data quality frameworks and metadata-driven testing.
Experience with defect management tools (JIRA) and test management tools (qTest, Zephyr, TestRail).
Exposure to version control (Git), CI/CD pipelines, Bit Bucket and DevOps practices.
Strong problem-solving, analytical, and debugging skills.
Target salary range: $80,001 - $120,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.
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