PalTech

As a Data Quality Engineer at PalTech, you will be responsible for designing and executing comprehensive test strategies for end-to-end data validation. Your role will ensure data completeness, accuracy, and integrity across ETL processes, data warehouses, and reporting environments. You will automate data validation using Python, validate fact and dimension tables, large datasets, file ingestions, and data exports, while ensuring adherence to data security standards, including encryption and authorization. This role requires strong analytical abilities, proficiency in SQL and Python, and the capability to collaborate effectively with cross-functional teams to drive continuous improvements through automation and best practices.

Key Responsibilities

• Create test strategies, test plans, business scenarios, and data validation scripts for end-to-end data validation.
• Verify data completeness, accuracy, and integrity throughout ETL processes, data pipelines, and reports.
• Evaluate and monitor the performance of ETL jobs to ensure adherence to defined SLAs.
• Automate data testing processes using Python or other relevant technologies.
• Validate various types of fact and dimension tables within data warehouse environments.
• Apply strong data warehousing (DWH) skills to ensure accurate data modeling and validation.
• Validate large datasets and ensure accuracy across relational databases.
• Validate file ingestions and data exports across different data sources.
• Assess and validate implementation of data security standards (encryption, authorization, anonymization).
• Demonstrate proficiency in SQL, Python, and ETL/ELT validation techniques.
• Validate reports and dashboards built on Power BI, Tableau, or similar platforms.
• Write complex scripts to validate business logic and KPIs across datasets.
• Create test data as required based on business use cases and scenarios.
• Identify, validate, and test corner business cases and edge scenarios.
• Prepare comprehensive test documentation including test cases, test results, and test summary reports.
• Collaborate closely with developers, business analysts, data architects, and other stakeholders.
• Recommend enhancements and implement best practices to strengthen and streamline testing processes.

Required Skills and Qualifications

• Education: Bachelor’s degree in Computer Science, Information Technology, or a related discipline.
• Technical Expertise: Strong understanding of ETL processes, data warehousing concepts, SQL, and Python.
• Experience: 4–6 years of experience in ETL testing, data validation, and report/dashboard validation; prior experience in automating data validation processes.
• Tools: Hands-on experience with ETL tools such as ADF, DBT, etc., defect tracking systems like JIRA, and reporting platforms such as Power BI or Tableau.
• Soft Skills: Excellent communication and teamwork abilities, with strong analytical and problem-solving skills.

Why Join PalTech?

• Great Place to Work Certified: We prioritize employee well-being and nurture an inclusive, collaborative environment where everyone can thrive.
• Competitive compensation, strong learning and professional g

As a Data Engineer at PalTech, you will design, develop, and maintain scalable and reliable data pipelines to ensure seamless data flow across systems. You will leverage SQL and leading ETL tools (such as Informatica, ADF, etc.) to support data integration and transformation needs. This role involves building and optimizing data warehouse architectures, performing performance tuning, and ensuring high levels of data quality, accuracy, and consistency throughout the data lifecycle.

You will collaborate closely with cross-functional teams to understand business requirements and translate them into effective data solutions. The ideal candidate should possess strong problem-solving skills, sound knowledge of data architecture principles, and a passion for building clean and efficient data systems.

Key Responsibilities

• Design, develop, and maintain ETL/ELT pipelines using SQL and tools such as Informatica, ADF, etc.
• Build and optimize data warehouse and data lake solutions for reporting, analytics, and operational usage.
• Apply strong understanding of data warehousing concepts to architect scalable data solutions.
• Handle large datasets and design effective load/update strategies.
• Collaborate with data analysts, business users, and data scientists to understand requirements and deliver scalable solutions.
• Implement data quality checks and validation frameworks to ensure data reliability and integrity.
• Perform SQL and ETL performance tuning and optimization.
• Work with structured and semi-structured data from various source systems.
• Monitor, troubleshoot, and resolve issues in data workflows.
• Maintain documentation for data pipelines, data flows, and data definitions.
• Follow best practices in data engineering including security, logging, and error handling.

Required Skills & Qualifications

Education:

• Bachelor’s degree in Computer Science, Information Technology, or a related field.

Technical Skills:

• Strong proficiency in SQL and data manipulation.
• Hands-on experience with ETL tools (e.g., Informatica, Talend, ADF).
• Experience with cloud data warehouse platforms such as BigQuery, Redshift, or Snowflake.
• Strong understanding of data warehousing concepts and data modeling.
• Proficiency in Python or a similar programming language.
• Experience working with RDBMS platforms (e.g., SQL Server, Oracle).
• Familiarity with version control systems and job schedulers.

Experience:

• 4 to 8 years of relevant experience in data engineering and ETL development.

Soft Skills:

• Strong problem-solving skills.
• Excellent communication and collaboration abilities.
• Ability to work effectively in a cross-functional team environment.