More jobs:
Ataccama SME
Job in
Boston, Suffolk County, Massachusetts, 02205, USA
Listed on 2026-06-01
Listing for:
My3Tech
Full Time
position Listed on 2026-06-01
Job specializations:
-
IT/Tech
Data Engineer, Data Analyst
Job Description & How to Apply Below
Our Client is seeking an Ataccama Subject Matter Expert to support the implementation and operationalization of a Data Certification Framework. The expert will collaborate with data quality teams to implement prioritized business use cases, configure data quality monitoring and reporting, provide training and enablement, and support integration with other enterprise tools. The engagement aims to ensure sustainable adoption and develop a roadmap for future capabilities in data quality management.
Project details
What are the key business use cases and existing challenges in data quality management that the Data Certification Framework aims to address?
The key business use cases that the Data Certification Framework aims to address include implementing end-to-end data quality monitoring for prioritized business use cases, configuring profiling and business rules (such as validity, completeness, and duplication), setting up observability dashboards, thresholds, alerts, and issue workflows, and enabling business reporting and exception tracking tied to defined KPIs. The framework also focuses on providing training and enablement for Data Stewards, Business Users, and Data Quality Analysts to ensure sustainable adoption and operational ownership.
Existing challenges in data quality management include the need for integration with other enterprise tools (e.g., Alation, Collibra, Service Now, Jira), establishing sustainable usage patterns, and developing a roadmap for future capabilities such as Data Lineage, Anomaly Detection, and Workflow Automation with SLA governance.
What specific functionalities and configurations are required in Ataccama to support data quality monitoring, reporting, and operational needs?
The required functionalities and configurations in Ataccama include profiling, business rule setup (validity, completeness, duplication, etc.), monitoring, observability dashboards, thresholds, alerts, issue workflows, and exception tracking tied to KPIs. Additionally, it involves enabling business reporting, hands-on training for stakeholders, and integration with tools like Alation, Collibra, MyAccess, Service Now, and Jira. These configurations aim to ensure operational ownership, sustainable adoption, and long-term scalability.
What types of data sources will the Data Certification Framework need to connect with, and are there any specific requirements for data integration?
The Data Certification Framework will likely need to connect with metadata management systems (e.g., Alation, Collibra), workflow tools (e.g., Jira, Service Now), and IT service management platforms. Integration requirements may include compatibility with these tools' APIs, support for data lineage and impact analysis, and the ability to handle structured and unstructured data for profiling, monitoring, and reporting purposes.
Which enterprise tools, such as Alation or Jira, need to be integrated with Ataccama, and what functionalities and reporting outputs are expected from these integrations?
Ataccama needs to be integrated with enterprise tools such as Alation, Collibra, MyAccess, Service Now, and Jira. These integrations are expected to support workflows, exception management, and enhance data quality monitoring and reporting capabilities. For example, Jira may be used for issue tracking and workflow automation, while Alation and Collibra could support metadata management and data cataloging. The specific reporting outputs would likely align with the defined KPIs and operational needs of the Data Quality Framework.
What are the main objectives of the Data Certification Framework in terms of improving data quality and governance?
The main objectives of the Data Certification Framework are to enhance data quality and governance by implementing prioritized business use cases with end-to-end data quality monitoring, including profiling, rule configuration, dashboards, alerts, and reporting. It also aims to enable sustainable adoption through training and enablement for stakeholders, establish operational ownership, and support integration with other enterprise tools. Additionally, the framework seeks to…
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