Quality Engineering (QE) Data Quality Engineer

Summary

Amida Technology Solutions is a technology company focused on data interoperability, integrity, governance, and security. The Data Quality Engineer will own the integrity of data flowing through test environments and analytics platforms by designing test data, validating databases and pipelines, automating data quality checks, and partnering with engineering and product teams. The role also includes incident triage, root cause analysis, metrics reporting, and documentation of data lineage and validation coverage.

Responsibilities

• Design, build, and maintain test data sets that cover realistic edge cases, referential integrity across systems, and volume profiles representative of production
• Implement and operate data masking, subsetting, and synthetic data generation so that non-production environments carry no live personal or regulated data
• Write and automate database-layer validation such as row counts, reconciliation, schema and constraint checks, referential integrity, slowly changing dimension behavior, and transformation logic
• Validate ETL/ELT pipelines end to end, from source ingestion through staging and curated layers, and isolate defects to the responsible stage
• Build reusable data quality frameworks and check suites, and wire them into CI/CD so data defects fail fast rather than surfacing in UAT
• Define and track data quality metrics (e.g., completeness, accuracy, timeliness, uniqueness, and consistency) and report trends to engineering and product leadership
• Partner with developers, DBAs, data engineers, and product owners on test data requirements, refresh cadence, and environment readiness
• Triage production data incidents, perform root cause analysis, and close gaps in coverage that allowed the defect through
• Document data lineage, masking rules, and validation coverage so audits and onboarding do not depend on undocumented institutional knowledge
• Other duties as assigned

Skills

• The candidate must be willing and able to work 3-4 days per week at our client's site in downtown Dallas, TX
• Bachelor's degree in computer science, engineering, or a related discipline
• At least three years of hands-on experience in test data management, data masking or de-identification, and database or data-layer validation
• At least two years of data validation and reporting experience with Snowflake and Power BI or similar technologies
• Practical experience with relational databases (e.g., PostgreSQL, SQL Server, Oracle, or MySQL) including schema design concepts, indexes, and constraints
• Demonstrated ownership of a test data strategy: provisioning, refresh, subsetting, and environment-specific data governance
• Experience validating data pipelines and warehouses and reconciling data across source and target systems
• Advanced SQL, including complex joins, window functions, aggregation, and query tuning against large tables
• Proficiency with Jira/Xray, Confluence, GitHub Actions, and Azure DevOps as the shared baseline toolset across the QE team
• Working knowledge of privacy and compliance requirements that drive masking (such as GDPR, CCPA, HIPAA, or PCI DSS) and the masking techniques that satisfy them (e.g., substitution, shuffling, tokenization, and format-preserving encryption)
• Scripting or programming ability in Python, or a comparable language, for automating validation and data generation
• Familiarity with CI/CD tooling and version control, and comfort embedding data checks into automated builds
• Ability to communicate clearly in writing, including defect reports, validation evidence, and documentation that a non-specialist can follow
• Strong analytical and problem-solving skills
• Experience with commercial or open-source TDM and masking tools (e.g., Delphix, Informatica TDM, IBM Optim, Tonic, or Redgate Data Masker)
• Knowledge of data quality frameworks such as Great Expectations, dbt tests, Soda, or Deequ
• Understanding of cloud data platforms such as Snowflake, BigQuery, Databricks, or Redshift
• Experience with orchestration tooling such as Airflow, dbt, or Azure Data Factory
• Streaming or event data validation with Kafka or an equivalent
• Synthetic data generation for cases where production-derived data cannot be used at all
• Security testing experience with Veracode or an equivalent
• Mobile automation testing experience with BrowserStack, Percy, or equivalent platforms
• Experience with UiPath or other RPA automation software
• Familiarity with Selenium, Playwright, REST Assured, Postman/Newman, and OpenAPI/Swagger for UI, API, and contract testing
• Prior work on federal, state, or local government programs

Qualifications

Must Haves

• The candidate must be willing and able to work 3-4 days per week at our client's site in downtown Dallas, TX
• Bachelor's degree in computer science, engineering, or a related discipline
• At least three years of hands-on experience in test data management, data masking or de-identification, and database or data-layer validation
• At least two years of data validation and reporting experience with Snowflake and Power BI or similar technologies
• Practical experience with relational databases (e.g., PostgreSQL, SQL Server, Oracle, or MySQL) including schema design concepts, indexes, and constraints
• Demonstrated ownership of a test data strategy: provisioning, refresh, subsetting, and environment-specific data governance
• Experience validating data pipelines and warehouses and reconciling data across source and target systems
• Advanced SQL, including complex joins, window functions, aggregation, and query tuning against large tables
• Proficiency with Jira/Xray, Confluence, GitHub Actions, and Azure DevOps as the shared baseline toolset across the QE team
• Working knowledge of privacy and compliance requirements that drive masking (such as GDPR, CCPA, HIPAA, or PCI DSS) and the masking techniques that satisfy them (e.g., substitution, shuffling, tokenization, and format-preserving encryption)
• Scripting or programming ability in Python, or a comparable language, for automating validation and data generation
• Familiarity with CI/CD tooling and version control, and comfort embedding data checks into automated builds
• Ability to communicate clearly in writing, including defect reports, validation evidence, and documentation that a non-specialist can follow
• Strong analytical and problem-solving skills

Nice to Haves

• Experience with commercial or open-source TDM and masking tools (e.g., Delphix, Informatica TDM, IBM Optim, Tonic, or Redgate Data Masker)
• Knowledge of data quality frameworks such as Great Expectations, dbt tests, Soda, or Deequ
• Understanding of cloud data platforms such as Snowflake, BigQuery, Databricks, or Redshift
• Experience with orchestration tooling such as Airflow, dbt, or Azure Data Factory
• Streaming or event data validation with Kafka or an equivalent
• Synthetic data generation for cases where production-derived data cannot be used at all
• Security testing experience with Veracode or an equivalent
• Mobile automation testing experience with BrowserStack, Percy, or equivalent platforms
• Experience with UiPath or other RPA automation software
• Familiarity with Selenium, Playwright, REST Assured, Postman/Newman, and OpenAPI/Swagger for UI, API, and contract testing
• Prior work on federal, state, or local government programs

Benefits

• A generous 401(k) match with immediate vesting
• 4 weeks of PTO
• Paid parental leave
• Medical insurance
• Dental insurance
• Vision insurance
• Life/AD&D insurance
• Short-term disability
• Tuition/training assistance
• Team-building opportunities to encourage professional growth and collaboration