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|Contract 6 months
Business Analyst at max £550 per day inside IR35, 1 day a week in Luton office.
Key skills required for this role
Business Analyst, Data Governance
DATA MANAGEMENT TEAM
Is led by the Chief Information Security Officer (CISO), within the overall Digital Safety group (reporting up into the board level Group General Council). The Data Management team is responsible for implementing all aspects of Data Management across the airline (including Data: Security, Access Controls, Governance [DG], Quality [DQ] and Controls), working with all areas within the business (including IT Data & Change, Legal, Finance, Engineering, Operations and Commercial). JOB PURPOSE Work with the business and IT by developing credible domain knowledge and stakeholder relationships. Currently there is heavy investment in a number of ambitious and essential Data Programmes at scale and in various phases. Currently there is no Enterprise Data Management operating model and BAU, so Data Discovery is required on the current silo tactical approaches and tactical assets that are being used to allow trust in the data, and an assessment of the gaps and types of Data Quality and Governance frameworks required.
> Data Quality Use Case deep dives including discover, document and maintenance of; o Existing tactical DG, DQ processes & controls o Datasets o Data Integrity o DQ issues o DQ rules o DQ technology o DQ processes and procedures o Data Lineage o Data domains o CDEs & KDEs > Support Data Discovery and DG/DQ workshops > Creating process flow maps of how key data attributes are created and their life cycle thereafter > Develop and maintain DQ and DG dashboards working with wider team to generate ideas that generate visibility of Data Quality across the dimensions > Work with business SMEs to help profile key data attributes and current data quality status > Analyse / evaluate data elements to identify potential risks (financial, people, regulatory and operational) are managed and mitigated effectively through escalation reports > Analyse / evaluate DQ issues to root causes and fix options > Support the creation of a framework by which data quality issues are continuously being identified/ reported and resolved > Work with Business units SME's where data quality issues are arising from systems and/ or system integration errors > Profile large datasets