Role Description We are seeking a Senior Data Engineer to join our Data & AI team. You will work within multidisciplinary project teams across a range of client engagements, contributing to the design and development of robust data infrastructure, data pipelines, and scalable data solutions. You think strategically, are comfortable with open-ended data problems, and can contribute meaningfully to client conversations about data architecture, modernization, and AI readiness. The ideal candidate is technically grounded, consulting-minded, and equally comfortable navigating ambiguity, working across disciplines, and communicating clearly with stakeholders at all levels. Travel for client and stakeholder meetings may be required depending on engagement. Key Responsibilities - Design, develop, and optimize data pipelines and data infrastructure across a range of client engagements. - Contribute to data modeling, master data management, and taxonomy standardization across complex, multi-system environments. - Build and test API integrations and prototypes, including working with static data exports and mock stubs in early-phase delivery contexts. - Document data governance artefacts - data domains, critical data elements, quality rules, and data lineage - and support clients in building data governance capability. - Reverse-engineer legacy systems and extract business logic from poorly documented codebases, complex spreadsheet models, or fragmented data structures. - Collaborate with architects, designers, product managers, and client stakeholders to align data solutions with broader digital product and platform goals. - Contribute to AI readiness assessments - evaluating data coverage, quality, schema consistency, and lineage to identify gaps and support remediation. - Perform code reviews, mentor junior team members, and contribute to best practices across the Data & AI team. - Communicate data architecture and pipeline design clearly using schemas, data flow diagrams, and visual artefacts, for both technical and non-technical audiences. Qualifications - 5+ years of data engineering experience, including delivery in a consulting or client-facing environment. - Proficiency in Python and SQL for data wrangling, transformation, and pipeline development. - Experience in data modeling - designing master data schemas and drafting unified taxonomies across fragmented source systems. - Master Data Management (MDM) experience: cleansing, mapping, and standardizing inconsistent data into a governed structure. - Experience building ETL/ELT pipelines and working with cloud data platforms (AWS, Azure, or GCP). - Experience documenting data governance artefacts and contributing to data governance frameworks. - Ability to reverse-engineer legacy systems and extract business logic from poorly documented codebases or complex Excel/VBA models. - Strong communication skills - able to translate technical decisions clearly for both technical and non-technical stakeholders. - Comfortable operating in ambiguity and structuring a path forward without perfect requirements. - Willing and able to ramp on new technologies as client engagements evolve. Nice to Have - Familiarity with Microsoft Azure services (Azure SQL, Cosmos DB, Azure DevOps). - Experience with API mock development or prototyping in early-phase delivery contexts. - Experience with ERP or supply chain data structures. - Experience modernizing legacy integrations (SOAP/WCF to REST). - Database consolidation or migration experience (SQLite, MSSQL, or cloud databases). - Familiarity with modern orchestration and transformation tools (Airflow, dbt, Dagster, Prefect). - Background in manufacturing, engineering, or cost modelling domains. - Familiarity with enterprise integration platforms such as MuleSoft. - Experience with machine learning or predictive analytics frameworks. Benefits - Continuing education opportunities - Flexible PTO and work-from-home policies - Pension - Health and dental benefits - Company lunches, company outings, along with a lot of snacks - Health and wellness programs - Other location specific perks (just ask!) Next Steps If Method sounds like the place for you, please submit an application. Also, let us know if you have a presence online with a portfolio, GitHub, Dribbble or other platform. By clicking the "Submit Application" button below, you give your express consent to process your data for this vacancy according to the Recruitment Privacy Notice. You can withdraw your consent at any time by contacting privacy@globallogic.com. You can find more information about how GlobalLogic processes your personal data and what your rights are in the Recruitment Privacy Notice.

Role Description - Conduct comprehensive reviews of more complex commercial loan closing packages to ensure accuracy, completeness, and compliance with internal policies and regulatory standards. - Validate data integrity through checklist-based audits, identifying and classifying critical and non-critical errors, and coordinating timely corrections with the booking team. - Monitor and report documentation discrepancies, partnering with Quality Control and Booking teams to resolve issues and maintain process alignment. - Maintain accurate loan logs and reporting, ensuring timely updates and proper transfer of completed booking packages for imaging and archival. - Support internal audits and quality assurance reviews, adhering to established SLS standards and meeting all performance metrics and KPIs. - Ensure compliance with all bank policies, procedures, and applicable regulations, embedding risk management and quality control into daily operations. - Participate in the training of new and more junior staff. Qualifications - Extensive knowledge of commercial lending and loan servicing and handling complex transactions. - Strong attention to detail with a focus on identifying discrepancies, ensuring data integrity, and maintaining compliance with internal policies. - Extensive knowledge of bank regulatory requirements. - Proficient PC skills including Microsoft Word and Excel. - Effective communication and organizational skills. - Ability to prioritize daily work assignments while working in a demanding environment is required. - Ability to meet deadlines defined by Bank and regulators. Requirements - High School diploma or GED equivalent with a minimum of 5 years of experience in a financial institution specializing in commercial loan operations and documentation and/or loan closing experience. Preferred Experience - Completion of college level courses in business administration and/or associate's degree.

• Design, develop and deploy data pipelines using Dataiku DSS Platform • Build and optimise ETL and ELT processes • Perform data integration, transformation, cleansing and validation • Develop scalable enterprise data solutions • Optimise machine learning workflows where required • Support migration to a modern data lakehouse architecture • Work closely with business and technical stakeholders

• Diseñar, construir y mantener procesos de integración de datos (ETL/ELT) • Modelar información para análisis de negocio • Automatizar flujos de datos • Desarrollar soluciones que permitan la toma de decisiones basada en datos