Airswift
From Airswift's careers page
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JOB DESCRIPTION JOB TITLE: Lead, Data Governance ACCOUNTABILITIES Purpose of the Role Lead of the central team responsible for driving all company entities to have accurate, consistent, available, and high quality data across around 120 data domains, 870 data families Drives the implementation of data governance for the digital use cases and digital data platform operations to ensure the integrity of data used and presented in the use cases and support decision making Implement data governance strategy for the organization. Leads the planning, evaluating, and selecting the right data governance capabilities for the enterprise. Advisor to the leadership team on enterprise wide data governance solutions and challenges. Key Accountabilities Drives the implementation of the enterprise data governance framework, strategy, and roadmap Drives the implementation of data governance practices in AI, advanced analytics, digital use cases and data platform operations Implementation and maintenance of solutions to manage data governance Company data literacy and organization upskilling Definition of polices, standards and guidelines for data governance and monitor adoption Budget management for operational costs and data investments JOB DIMENSIONS Managing an annual budget of approx. USD $2M Managing 2 direct reports 5 service contracts Lead of a central team driving the improvement of data governance for 16 department Involves close working relations with the digital team, department focal points and leadership, data owners, and data stewards as well as contractors ACTIVITIES Manage enterprise data governance framework, strategy, and maturity Lead data governance to promote data access, quality, and analytical capability. Governance can include a user training program, a data roles model, and data standards. Strives to reduce the cost of managing data and increase the value of the data. Lead the improvement of data literacy across company to upskill the organization on the value and use of data Measure enterprise data governance maturity and set yearly plans to improvement goals Represents the DM team and enterprise data stewards at leadership meetings. Develops and gives oral presentations on the power and value of data. Leads and/or serve steering committees and helps leadership use its data effectively at these meetings. (i.e. Data Community, Data Council...etc.) Apply expert knowledge and standards to analyze enterprise results and reports. Recommends and pursues collaboration and provides appropriate technical guidance to ensure the success of such collaborations. Interacts with business areas and IT on DM solutions. Embed the data governance practices in AI, advanced analytics, digital use cases and data platform operations Participate in scoping AI, Advanced Analytics, digital use cases and vendor proposals evaluations Ensure data quality rules are defined and developed, Data lineage for technical metadata are captured, business glossary is captured and approved by data stewards according to every digital use case data needs Establish and advance the enterprise AI Governance framework by defining AI agent operating boundaries, implementing governance controls and data quality assurance mechanisms, and delivering a strategic AI Governance roadmap that strengthens governance maturity, mitigates risk, and enables the responsible scaling of AI initiatives across the organization. Ensure the onboard of the digital use case owners and data stewards on the data governance tools to monitor their data usage, quality, and assignment Enable digital use cases master data management scope by defining the data quality checks Responsible for ensuring the data certification standard is followed, through the validation of data at source and destination are align for any data load or migration activity for digital use cases or application changes Implement and maintain solutions to manage data governance Lead the identification and configuration of data hierarchy, roles, catalog, quality, and business glossary for enterprise company data on Data Governance tools leveraging Oil and Gas standard practices Lead the prioritization, development and maintaining controls on data quality and sources to effectively manage risk associated with the use of data and analytics, as well as work with every entity to improve the finding and report issues to senior management per department Responsible for capturing business data challenges and propose solutions to overcome it Report the progress and challenges to senior management through Data Council and DPG Steer Co. Defines polices, standards and guidelines for data governance Lead the develop of data management policies, procedures, and guidelines relevant to the data management company needs Lead the development and implementation of enterprise metadata standards, guidelines, and processes to ensure quality metadata and support for ongoing data governance Ensure and monitor the adherence to all data policies, procedures, and guidelines Govern and overlooks the data sources to ensure its alignment with policies and best practices of handling stored data Aligns with the data operations to ensure it fulfils the data governance requirements Upskills developees on data governance and management MUST HAVE QUALIFICATIONS & EXPERIENCE REQUIRED Bachelor’s degree from an accredited university in Information Management or an engineering/business related equivalent. 10+ years of experience in Data Management for Oil and Gas Upstream/Downstream Operations and Major Capital Projects. 5+ years of experience in a management/lead position working through the definition and implementations of similar engineering information projects. Strong handson experience in building data governance strategy, framework, roadmaps, decision making bodies and on boarding data roles (data owners/stewards) Solid track record implementing scalable data governance technology stacks (including business glossary, data lineage, data quality) Good understanding of the data solutions used for different Data Management needs such as Data visualization and BI, data science, data warehouses/lakes, Master data Management, data modeling Enterprise Document Management solutions...etc Experience in Change Management, Program management and Stakeholder management Experience in data integration methods Good understanding of Upstream and Downstream DIM requirements Good Knowledge of Database systems, EDMS solutions and BI Technologies Good Knowledge of Applications Architecture, Information Security Principles Fluent English both spoken and written
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