Ampcus Inc
Overview
Position Summary: The Data Assurance & Validation Lead/Data Assurance Manager is responsible for ensuring the accuracy, integrity, and consistency of enterprise data across migration, transformation, and reporting projects. This role blends leadership with hands-on execution—overseeing data quality strategy, ETL testing, and client engagement while also directly performing complex SQL validation and data reconciliation. The ideal candidate will build client confidence, mentor team members, and independently drive project delivery from planning through validation sign-off. Key Responsibilities
Lead
end-to-end data validation and assurance
for data migration, transformation, and consolidation initiatives. Act as the
primary liaison with the client , translating business and technical requirements into actionable data validation plans. Review and interpret
Source-to-Target Mapping (STTM)
documents to confirm transformation accuracy, business rule alignment, and data lineage completeness. Perform
hands-on SQL analysis
and reconciliation across multiple relational databases (Oracle, SQL Server, PostgreSQL). Validate ETL workflows and transformations using tools such as
Informatica, DataStage, Azure Data Factory, or AWS Glue . Collaborate with data engineers, developers, and BI/reporting teams to resolve data discrepancies and ensure end-to-end accuracy. Design and execute
data quality test plans , including record-count checks, transformation verification, and exception handling. Establish repeatable templates, reusable queries, and documentation standards for data validation projects. Monitor and report progress, issues, and data quality metrics to internal leadership and client stakeholders. Mentor junior team members and coordinate testing deliverables across distributed teams. Proactively identify risks, recommend process improvements, and support continuous enhancement of data quality practices. Required Qualifications
10+ years of experience in
data assurance, ETL testing, or data migration validation
across complex enterprise environments. Advanced
SQL
skills for profiling, transformation validation, and reconciliation. Hands-on experience with
Oracle, SQL Server, and PostgreSQL
databases. Proficient in
ETL tools
such as Informatica, DataStage, Azure Data Factory, or AWS Glue. Demonstrated understanding of
Source-to-Target Mapping (STTM)
and ability to validate transformation logic end-to-end. Exposure to
data analytics and reporting validation
(e.g., Tableau, Power BI, OBIEE). Strong communication and presentation skills with experience engaging directly with clients. Ability to work independently and take full ownership of deliverables without constant supervision. Experience working within
Agile/Scrum
frameworks and using tools like JIRA or Azure DevOps. Preferred Qualifications
Experience leading small teams or coordinating distributed QA/ETL resources. Familiarity with
data governance, data lineage, and quality frameworks . Experience in
federal or financial domains . Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related discipline. Summary Statement
This role is ideal for a data professional who combines
technical mastery
with
delivery ownership —someone who can write complex SQL, interpret STTMs, guide ETL testing, and communicate confidently with clients. The
Data Assurance & Validation Lead
will be trusted to ensure data correctness across every stage of the pipeline while representing the team’s technical and quality leadership.
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Position Summary: The Data Assurance & Validation Lead/Data Assurance Manager is responsible for ensuring the accuracy, integrity, and consistency of enterprise data across migration, transformation, and reporting projects. This role blends leadership with hands-on execution—overseeing data quality strategy, ETL testing, and client engagement while also directly performing complex SQL validation and data reconciliation. The ideal candidate will build client confidence, mentor team members, and independently drive project delivery from planning through validation sign-off. Key Responsibilities
Lead
end-to-end data validation and assurance
for data migration, transformation, and consolidation initiatives. Act as the
primary liaison with the client , translating business and technical requirements into actionable data validation plans. Review and interpret
Source-to-Target Mapping (STTM)
documents to confirm transformation accuracy, business rule alignment, and data lineage completeness. Perform
hands-on SQL analysis
and reconciliation across multiple relational databases (Oracle, SQL Server, PostgreSQL). Validate ETL workflows and transformations using tools such as
Informatica, DataStage, Azure Data Factory, or AWS Glue . Collaborate with data engineers, developers, and BI/reporting teams to resolve data discrepancies and ensure end-to-end accuracy. Design and execute
data quality test plans , including record-count checks, transformation verification, and exception handling. Establish repeatable templates, reusable queries, and documentation standards for data validation projects. Monitor and report progress, issues, and data quality metrics to internal leadership and client stakeholders. Mentor junior team members and coordinate testing deliverables across distributed teams. Proactively identify risks, recommend process improvements, and support continuous enhancement of data quality practices. Required Qualifications
10+ years of experience in
data assurance, ETL testing, or data migration validation
across complex enterprise environments. Advanced
SQL
skills for profiling, transformation validation, and reconciliation. Hands-on experience with
Oracle, SQL Server, and PostgreSQL
databases. Proficient in
ETL tools
such as Informatica, DataStage, Azure Data Factory, or AWS Glue. Demonstrated understanding of
Source-to-Target Mapping (STTM)
and ability to validate transformation logic end-to-end. Exposure to
data analytics and reporting validation
(e.g., Tableau, Power BI, OBIEE). Strong communication and presentation skills with experience engaging directly with clients. Ability to work independently and take full ownership of deliverables without constant supervision. Experience working within
Agile/Scrum
frameworks and using tools like JIRA or Azure DevOps. Preferred Qualifications
Experience leading small teams or coordinating distributed QA/ETL resources. Familiarity with
data governance, data lineage, and quality frameworks . Experience in
federal or financial domains . Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related discipline. Summary Statement
This role is ideal for a data professional who combines
technical mastery
with
delivery ownership —someone who can write complex SQL, interpret STTMs, guide ETL testing, and communicate confidently with clients. The
Data Assurance & Validation Lead
will be trusted to ensure data correctness across every stage of the pipeline while representing the team’s technical and quality leadership.
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