Find Jobs
Find Jobs Near You – Available Work in Your Location
Skip to job details
K
Kyndryl
Data Analyst - Public Sector & EU Funding
Career Insights for Data Analyst
See where this job fits in the broader career landscape. Knowing your career path helps you see what's possible from here.
Scorecard
Based on Illinois data
Review key factors to help you decide if this role fits your goals. How is this calculated?
What they do
A Data Analyst develops computer programs to analyze large customer information databases for companies and organizations. Analyzes data to identify patterns and provide information relevant to a particular business, industry or field; analysis may be used for marketing, or to detect fraud in financial transactions, or for research. Develops computer programs to protect confidential customer information.
$79,826 / year median in Illinois
+13% projected growth
Job Description
Who We AreAt Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world's leading businesses. We are at the heart of progress; with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. For our people-Kyndryls-that means doing purposeful work that powers human progress. Join us and experience a flexible, supportive environment where your well-being is prioritized and your potential can thrive.
The RoleWe are looking for an experienced Data Analyst to join a data analytics project supporting a European public-sector organisation.
The role focuses on the collection, integration, cleaning, harmonisation, validation and analysis of complex administrative and public-sector datasets, including project-level and EU funding data.
The successful candidate will work with heterogeneous structured and semi-structured data sources, designing reproducible data-processing workflows and analytical datasets using SQL, Python, R or equivalent technologies. The position also involves database management, data quality, entity resolution and record linkage, data visualisation and the validation of outputs generated through AI/NLP-assisted processing.
The role requires strong analytical and communication skills and the ability to work with both technical specialists and non-technical stakeholders in an international environment.
The position is based in Sevilla, Spain.
The Data Analyst will be responsible for activities including:
Collecting, assessing, integrating and managing data from EU, national and other administrative/public-sector databases.
Cleaning, transforming and harmonising structured and semi-structured datasets using SQL, Python, R or equivalent analytical tools.
Identifying and standardising organisations, beneficiaries and other entities across heterogeneous data sources.
Designing and applying entity matching, record linkage, deduplication and reconciliation techniques.
Designing, building and maintaining relational or analytical databases, including tables, keys, relationships, views, metadata and data dictionaries.
Defining and implementing data-quality and validation controls covering completeness, consistency, accuracy, uniqueness, plausibility and traceability.
Developing reproducible extraction, transformation and analytical workflows, including reusable scripts and documented processing rules.
Performing exploratory, descriptive and comparative data analysis and developing analytical indicators.
Creating analytical tables, visualisations, dashboards and reports for technical, policy and non-technical audiences.
Working with textual and unstructured information and supporting AI, Machine Learning and NLP-assisted data-processing workflows.
Reviewing and validating automatically extracted entities, events, dates, amounts, classifications and relationships, including analysis of false positives and false negatives.
Documenting data sources, assumptions, methodologies, limitations, data lineage and quality issues.
Collaborating with policy officers, data owners, IT specialists and other stakeholders.
Presenting analytical findings, methodological approaches, progress and risks clearly to technical and non-technical audiences. Who You AreMandatory qualifications and experienceUniversity degree corresponding to EQF Level 7 (typically Master's degree or equivalent) plus at least 5 years of professional IT experience; ORUniversity degree corresponding to EQF Level 6 (typically Bachelor's degree or equivalent) plus at least 7 years of professional IT experience.
English level B2 or higher, both spoken and written.
Minimum 3 years of experience collecting, cleaning, harmonising and analysing structured and semi-structured data using SQL and Python, R or equivalent analytical programming languages.
Minimum 3 years of experience in data extraction and transformation, construction/maintenance of relational or analytical databases and preparation of reproducible datasets.
Minimum 3 years of experience in entity identification, name standardisation, record linkage, deduplication, data-quality validation and reconciliation across heterogeneous data sources.
Minimum 2 years of experience in exploratory, descriptive or comparative data analysis and/or indicator development.
Minimum 1 year of experience using Machine Learning, NLP or other AI-assisted methods for processing textual or unstructured information.
Minimum 6 months of experience processing and analysing EU funding data or public-sector/administrative data sources.
Minimum 6 months of experience in data visualisation and communicating analytical or methodological findings to non-technical audiences.
At least one recognised professional certification related to Data Analytics, Business Intelligence, Data Engineering, Database Management or Data Governance. Relevant examples include Microsoft Power BI Data Analyst Associate, Azure Data Engineer Associate, Microsoft Fabric Analytics Engineer Associate or Microsoft Fabric Data Engineer Associate, or an equivalent certification.
Highly valued skills and experienceAdvanced practical knowledge of SQL and Python/R.Experience integrating heterogeneous administrative datasets.
Strong knowledge of data quality, metadata, data dictionaries and data lineage.
Experience with Power BI, Qlik, Microsoft Fabric or equivalent data-visualisation/BI technologies.
Experience with entity resolution and fuzzy/probabilistic matching techniques.
Experience with public-sector, EU funding, municipal or territorial data.
Experience validating results generated through ML, NLP, LLM or AI-assisted workflows.
Strong communication skills and ability to translate analytical findings into understandable conclusions for non-technical stakeholders.
Ability to work effectively in international and multidisciplinary teams.
Being YouThe \
The RoleWe are looking for an experienced Data Analyst to join a data analytics project supporting a European public-sector organisation.
The role focuses on the collection, integration, cleaning, harmonisation, validation and analysis of complex administrative and public-sector datasets, including project-level and EU funding data.
The successful candidate will work with heterogeneous structured and semi-structured data sources, designing reproducible data-processing workflows and analytical datasets using SQL, Python, R or equivalent technologies. The position also involves database management, data quality, entity resolution and record linkage, data visualisation and the validation of outputs generated through AI/NLP-assisted processing.
The role requires strong analytical and communication skills and the ability to work with both technical specialists and non-technical stakeholders in an international environment.
The position is based in Sevilla, Spain.
The Data Analyst will be responsible for activities including:
Collecting, assessing, integrating and managing data from EU, national and other administrative/public-sector databases.
Cleaning, transforming and harmonising structured and semi-structured datasets using SQL, Python, R or equivalent analytical tools.
Identifying and standardising organisations, beneficiaries and other entities across heterogeneous data sources.
Designing and applying entity matching, record linkage, deduplication and reconciliation techniques.
Designing, building and maintaining relational or analytical databases, including tables, keys, relationships, views, metadata and data dictionaries.
Defining and implementing data-quality and validation controls covering completeness, consistency, accuracy, uniqueness, plausibility and traceability.
Developing reproducible extraction, transformation and analytical workflows, including reusable scripts and documented processing rules.
Performing exploratory, descriptive and comparative data analysis and developing analytical indicators.
Creating analytical tables, visualisations, dashboards and reports for technical, policy and non-technical audiences.
Working with textual and unstructured information and supporting AI, Machine Learning and NLP-assisted data-processing workflows.
Reviewing and validating automatically extracted entities, events, dates, amounts, classifications and relationships, including analysis of false positives and false negatives.
Documenting data sources, assumptions, methodologies, limitations, data lineage and quality issues.
Collaborating with policy officers, data owners, IT specialists and other stakeholders.
Presenting analytical findings, methodological approaches, progress and risks clearly to technical and non-technical audiences. Who You AreMandatory qualifications and experienceUniversity degree corresponding to EQF Level 7 (typically Master's degree or equivalent) plus at least 5 years of professional IT experience; ORUniversity degree corresponding to EQF Level 6 (typically Bachelor's degree or equivalent) plus at least 7 years of professional IT experience.
English level B2 or higher, both spoken and written.
Minimum 3 years of experience collecting, cleaning, harmonising and analysing structured and semi-structured data using SQL and Python, R or equivalent analytical programming languages.
Minimum 3 years of experience in data extraction and transformation, construction/maintenance of relational or analytical databases and preparation of reproducible datasets.
Minimum 3 years of experience in entity identification, name standardisation, record linkage, deduplication, data-quality validation and reconciliation across heterogeneous data sources.
Minimum 2 years of experience in exploratory, descriptive or comparative data analysis and/or indicator development.
Minimum 1 year of experience using Machine Learning, NLP or other AI-assisted methods for processing textual or unstructured information.
Minimum 6 months of experience processing and analysing EU funding data or public-sector/administrative data sources.
Minimum 6 months of experience in data visualisation and communicating analytical or methodological findings to non-technical audiences.
At least one recognised professional certification related to Data Analytics, Business Intelligence, Data Engineering, Database Management or Data Governance. Relevant examples include Microsoft Power BI Data Analyst Associate, Azure Data Engineer Associate, Microsoft Fabric Analytics Engineer Associate or Microsoft Fabric Data Engineer Associate, or an equivalent certification.
Highly valued skills and experienceAdvanced practical knowledge of SQL and Python/R.Experience integrating heterogeneous administrative datasets.
Strong knowledge of data quality, metadata, data dictionaries and data lineage.
Experience with Power BI, Qlik, Microsoft Fabric or equivalent data-visualisation/BI technologies.
Experience with entity resolution and fuzzy/probabilistic matching techniques.
Experience with public-sector, EU funding, municipal or territorial data.
Experience validating results generated through ML, NLP, LLM or AI-assisted workflows.
Strong communication skills and ability to translate analytical findings into understandable conclusions for non-technical stakeholders.
Ability to work effectively in international and multidisciplinary teams.
Being YouThe \