ph3About Swissport /h3 pWe are a integral leader in sustainable and responsible airport services provision, renowned for our unwavering commitment to safety, operational excellence, and exceptional service, shaping a future where air travel thrives on reliability, efficiency, and experience. /p h3Location /h3 pLocation: Madrid, Hybrid /p h3About Swissport /h3 pWe are a global leader in sustainable and responsible airport services provision, renowned for our unwavering commitment to safety, operational excellence, and exceptional service, shaping a future where air travel thrives on reliability, efficiency, and experience. /p pIn 2023, with the support of more than 60,000 colleagues, Swissport provided best-in-class airport ground services for some 232 million airline passengers and handled roughly 4.7 million tons of air freight at 115 cargo centres. Across a global network that is unparalleled in the industry, Swissport served airlines at 286 airports in 44 countries across six continents. /p pThe culture of Swissport is shaped by our corporate values, which guide our actions and decision-making processes. These values are at the core of our culture, shaping our business and underpinning our commitment to measuring our impact. They capture the essence of who we are at Swissport and help us deliver value across the entire company. /p p"Show You Care" underlines that our actions are perceived and valued from the perspective of the people around us. So, whatever we do, we do it purposefully and consciously, taking in the perspective of our colleagues, customers, and passengers. /p p"Doing the right things" means that we do the things that are valuable to our colleagues, customers, and passengers. We are trained to do this safely and trusted to do the right thing in any given situation. /p p"Win as a Team" highlights the importance of teamwork. Either we win as a team, or we fall as individuals. Together, we can surpass ourselves and handle any situation. /p pThese values capture the essence of who we are and our unwavering commitment to excellence, and give actionable guidance for individual behaviour of employees, leaders, and executives,



serving as a compass for how to act and deliver. /p h3Job Summary /h3 pSupport a major system implementation by extracting, analysing, cleansing, transforming and validating large volumes of data from legacy systems for migration into a new enterprise platform. The successful candidate will ensure data is accurate, complete and fit for purpose by applying data quality standards, business rules and reconciliation processes throughout the migration lifecycle. /p h3Job Responsibilities /h3 ul liExtract high-volume datasets from multiple legacy systems using appropriate database query and extraction tools. /li liAnalyse complex datasets to identify data quality issues, inconsistencies, duplicates and missing information. /li liCleanse, standardise and transform data in accordance with agreed business rules and migration specifications. /li liPrepare and format data for bulk upload into the target system using automated processes and migration tools. /li liPerform data validation, reconciliation and integrity checks before and after migration activities. /li liInvestigate and resolve data anomalies, working with business stakeholders and technical teams where required. /li liDevelop repeatable extraction, transformation and loading (ETL) processes to improve efficiency and accuracy. /li liProduce data mapping documentation between source and target systems. /li liMaintain comprehensive documentation of migration activities, assumptions, data issues and resolutions. /li liSupport multiple migration cycles including trial migrations, user acceptance testing and production cutover. /li liMonitor data quality metrics and report progress, risks and issues to project management. /li liEnsure compliance with organisational data governance, security and privacy requirements.



/li liCollaborate with business analysts, solution architects, developers and system owners throughout the migration programme. /li /ul h3Qualifications And Competencies /h3 ul liRequired years of experience: 3-5 years /li liExperience working with large datasets beyond the practical limitations of Excel. /li liExperience in data migration, system implementation or digital transformation projects. /li liStrong understanding of data quality, cleansing, validation and reconciliation techniques. /li liExperience extracting data from relational databases and legacy applications. /li liKnowledge of data mapping and migration methodologies. /li liExperience working in structured project environments. /li liUnderstanding of data governance principles and information security. /li liExperience with Dayforce (HRIS/HCM) is preferred. /li liAdvanced SQL for querying and manipulating large datasets. /li liExperience with SQL Server, Oracle, PostgreSQL or MySQL. /li liFamiliarity with ETL tools or scripting languages such as SSIS, Azure Data Factory, Talend, Informatica, Python or PowerShell. /li liAbility to work with multi-million-row datasets using appropriate database and analytics tools. /li liStrong Excel skills for data analysis. /li liProven experience developing dashboards, reports and data visualisations using Microsoft Power BI (required). /li liHighly analytical with excellent attention to detail. /li liMethodical and organised approach to managing complex data. /li liStrong problem-solving and investigative skills. /li liExcellent communication skills with both technical and non-technical stakeholders. /li liAble to work independently and collaboratively within a project team. /li liCommitted to delivering high-quality, accurate data under tight deadlines. /li /ul pThis job description indicates the general nature and level of work expected of the incumbent. It is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities required of the incumbent. Incumbent may be required to perform other related duties. /p /p #J-18808-Ljbffr

📌 Data Analytics Specialist - Transformation (Madrid)
🏢 Swissport
📍 Madrid