Data Scientist Level

Job Description

Data Scientist Level: 3
Hybrid- (Austin, Texas- least 2 days per in the office, and the other days working from home)
6 months Contract

FUNCTIONAL RESPONSIBILITIES
Essential Services include, but are not limited to:

• Data Reconciliation Strategy:

• Provide strategies to ensure accurate and efficient data reconciliation between Oracle to SQL Server environments.

• Recommend best practices for comparing millions of converted data rows and validating data integrity.

• Data Validation & Testing:

• Deliver efficient and scalable data comparison techniques to validate data accuracy post-migration.

• Propose solutions for data chunking, batch processing, and data hashing to address memory and performance challenges.

• Automate data validation processes to reduce manual intervention and improve testing efficiency.

• Perform detailed data reconciliation testing to identify discrepancies such a mismatches, missing rows, or invalid data.


• Scalable Testing Approaches:

• Design methods for incremental data validation and parallelized comparison tasks.

• Suggest solutions to enhance scalability and performance.

• Support in performance tuning of SQL queries to optimize data comparison processes.

• Best Practices & Frameworks:

• Recommend tools and frameworks for handling large-scale data comparisons in Oracle and SQL Server.

• Share case studies or examples of successful large-scale data reconciliation testing projects.

• Collaboration and Knowledge Transfer:

• Provide training and mentorship to teams on data governance, validation strategies, and scalable testing practices.

WORKER SKILLS AND QUALITICATIONS
Required Minimum Qualifications:

• Demonstrated expertise in enterprise data management, ETL processes, and large-scale data reconciliation testing projects.

• Proven experience with Oracle, SQL Server, SSIS, and T-SQL scripting.

• Strong knowledge of data validation, chunking, batch processing, and data hashing techniques.

• Ability to provide proven methodologies, frameworks, and tools that support large-scale data comparison.

• Experience with automation tools and scalable testing frameworks.

• Proficiency in data reconciliation, automated testing, and performance tuning of SQL queries.

• Familiarity with data auditing and monitoring tools.