126 to 150 of 761 Validation Jobs in the South East

SAP S/4HANA Greenfield projects. Strong hands-on knowledge of SAP Data Services and SAP Migration Cockpit. Deep understanding of the data migration lifecycle, including planning, mapping, transformation, validation, and reconciliation. Ability to mentor technical teams, suggest solutions, and step in to support development tasks when necessary. Experience in running data workshops, engaging with both technical and business stakeholders. More ❯

SAP S/4HANA Greenfield projects. Strong hands-on knowledge of SAP Data Services and SAP Migration Cockpit. Deep understanding of the data migration lifecycle, including planning, mapping, transformation, validation, and reconciliation. Ability to mentor technical teams, suggest solutions, and step in to support development tasks when necessary. Experience in running data workshops, engaging with both technical and business stakeholders. More ❯

implement ETL workflows to manage data extraction, transformation, and loading into Teradata. Build and maintain risk models for credit, operational, and market risk analysis. Conduct data profiling, cleansing, and validation to ensure accuracy and consistency. Collaborate with stakeholders to gather requirements and deliver data-driven solutions. Perform exploratory data analysis to uncover trends and support risk mitigation. Automate reporting and More ❯

implement ETL workflows to manage data extraction, transformation, and loading into Teradata. Build and maintain risk models for credit, operational, and market risk analysis. Conduct data profiling, cleansing, and validation to ensure accuracy and consistency. Collaborate with stakeholders to gather requirements and deliver data-driven solutions. Perform exploratory data analysis to uncover trends and support risk mitigation. Automate reporting and More ❯

implement ETL workflows to manage data extraction, transformation, and loading into Teradata. Build and maintain risk models for credit, operational, and market risk analysis. Conduct data profiling, cleansing, and validation to ensure accuracy and consistency. Collaborate with stakeholders to gather requirements and deliver data-driven solutions. Perform exploratory data analysis to uncover trends and support risk mitigation. Automate reporting and More ❯

Python scripts to clean, transform, aggregate, and process large volumes of data. Database Interaction (SQL): Develop complex, high-performance SQL queries (DDL/DML) for data extraction, manipulation, and validation within relational and data warehousing environments. Quality Assurance: Implement data quality checks and monitoring across pipelines, identifying discrepancies and ensuring the accuracy and reliability of data. Collaboration: Work closely with More ❯

Python scripts to clean, transform, aggregate, and process large volumes of data. Database Interaction (SQL): Develop complex, high-performance SQL queries (DDL/DML) for data extraction, manipulation, and validation within relational and data warehousing environments. Quality Assurance: Implement data quality checks and monitoring across pipelines, identifying discrepancies and ensuring the accuracy and reliability of data. Collaboration: Work closely with More ❯

Stakeholders: Work closely with business process owners, system integrators, and IT teams to gather requirements, validate security designs, and ensure roles meet functional needs without compromising security. Testing and Validation: Support the User Acceptance Testing (UAT) phase by providing expertise on role-based security, troubleshooting access issues, and ensuring roles function as designed. Documentation: Create and maintain detailed documentation of More ❯

Stakeholders: Work closely with business process owners, system integrators, and IT teams to gather requirements, validate security designs, and ensure roles meet functional needs without compromising security. Testing and Validation: Support the User Acceptance Testing (UAT) phase by providing expertise on role-based security, troubleshooting access issues, and ensuring roles function as designed. Documentation: Create and maintain detailed documentation of More ❯

Stakeholders: Work closely with business process owners, system integrators, and IT teams to gather requirements, validate security designs, and ensure roles meet functional needs without compromising security. Testing and Validation: Support the User Acceptance Testing (UAT) phase by providing expertise on role-based security, troubleshooting access issues, and ensuring roles function as designed. Documentation: Create and maintain detailed documentation of More ❯

apply a structured maturity model to assess how data science work is conceived, executed, validated, and scaled. • Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring, and iteration. • Tooling & Workflow Analysis: Review the ecosystem of analytical tools, frameworks, and environments used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices More ❯

apply a structured maturity model to assess how data science work is conceived, executed, validated, and scaled. • Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring, and iteration. • Tooling & Workflow Analysis: Review the ecosystem of analytical tools, frameworks, and environments used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices More ❯

apply a structured maturity model to assess how data science work is conceived, executed, validated, and scaled. • Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring, and iteration. • Tooling & Workflow Analysis: Review the ecosystem of analytical tools, frameworks, and environments used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices More ❯

apply a structured maturity model to assess how data science work is conceived, executed, validated, and scaled. • Model Lifecycle Review: Assess practices across data preparation, feature engineering, model development, validation, monitoring, and iteration. • Tooling & Workflow Analysis: Review the ecosystem of analytical tools, frameworks, and environments used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices More ❯

Experience with Avaloq: Familiarity with Avaloq's physical data layer is essential Knowledge of data quality frameworks: Understanding of profiling dimensions and industry-standard approaches (e.g., DQ checks, data validation rules) Nice-to-Have Skills Description: Experience with Avaloq Reporting & Data Extracts (ARD, ADF, SmartView): Familiarity with Avaloq-specific data export or reporting mechanisms would help accelerate development. Knowledge of More ❯

Experience with Avaloq: Familiarity with Avaloq's physical data layer is essential Knowledge of data quality frameworks: Understanding of profiling dimensions and industry-standard approaches (e.g., DQ checks, data validation rules) Nice-to-Have Skills Description: Experience with Avaloq Reporting & Data Extracts (ARD, ADF, SmartView): Familiarity with Avaloq-specific data export or reporting mechanisms would help accelerate development. Knowledge of More ❯

Experience with Avaloq: Familiarity with Avaloq's physical data layer is essential Knowledge of data quality frameworks: Understanding of profiling dimensions and industry-standard approaches (e.g., DQ checks, data validation rules) Nice-to-Have Skills Description: Experience with Avaloq Reporting & Data Extracts (ARD, ADF, SmartView): Familiarity with Avaloq-specific data export or reporting mechanisms would help accelerate development. Knowledge of More ❯

end ownership. The Role Design, build, and optimise data pipelines and ETL processes that feed critical research and trading systems. Engineer scalable, automated solutions for data ingestion, cleaning, and validation across multiple structured and unstructured sources. Collaborate with researchers, technologists, and analysts to enhance the quality, timeliness, and accessibility of data. Contribute to the evolution of modern cloud-based data More ❯

Experience with Avaloq: Familiarity with Avaloq's physical data layer is essential Knowledge of data quality frameworks: Understanding of profiling dimensions and industry-standard approaches (e.g., DQ checks, data validation rules) Nice-to-Have Skills Description: Experience with Avaloq Reporting & Data Extracts (ARD, ADF, SmartView): Familiarity with Avaloq-specific data export or reporting mechanisms would help accelerate development. Knowledge of More ❯

end ownership. The Role Design, build, and optimise data pipelines and ETL processes that feed critical research and trading systems. Engineer scalable, automated solutions for data ingestion, cleaning, and validation across multiple structured and unstructured sources. Collaborate with researchers, technologists, and analysts to enhance the quality, timeliness, and accessibility of data. Contribute to the evolution of modern cloud-based data More ❯

end ownership. The Role Design, build, and optimise data pipelines and ETL processes that feed critical research and trading systems. Engineer scalable, automated solutions for data ingestion, cleaning, and validation across multiple structured and unstructured sources. Collaborate with researchers, technologists, and analysts to enhance the quality, timeliness, and accessibility of data. Contribute to the evolution of modern cloud-based data More ❯

data into structured, analysis-ready datasets. Develop and optimise data models (including Data Vault and dimensional modelling) to support large-scale analytics. Implement and enforce data quality, governance, and validation frameworks . Write complex SQL to ensure accuracy, performance, and scalability. Collaborate with data engineers and architects to ensure seamless data integration across platforms. Automate repetitive data processes and workflows More ❯

data into structured, analysis-ready datasets. Develop and optimise data models (including Data Vault and dimensional modelling) to support large-scale analytics. Implement and enforce data quality, governance, and validation frameworks . Write complex SQL to ensure accuracy, performance, and scalability. Collaborate with data engineers and architects to ensure seamless data integration across platforms. Automate repetitive data processes and workflows More ❯

help people transform their knowledge and passion into skills that employers need. This apprenticeship will teach you essential data skills, including how to source, format and present data; data validation and analysis; and how to apply legal and ethical principles when gathering and manipulating business data. More ❯

help people transform their knowledge and passion into skills that employers need. This apprenticeship will teach you essential data skills, including how to source, format and present data; data validation and analysis; and how to apply legal and ethical principles when gathering and manipulating business data. INDDA More ❯