• Shaping the architecture of data products designed for data analytics and data science specifically focusing on use cases like forecasting, feature engineering, customer behaviour, and integration of new data sources. • Leading the way in data transformation by setting up best practices in areas like Data modelling, performance optimisation, Data Governance etc, ensuring that the data used within Prima is consistent, available and reliable. • Build reusable technology that enables teams to ingest, store, transform, and serve their own data products. • Engaging with data scientists and machine learning engineers to explore the product landscape and refine data requirements for enhanced data infrastructure. • Embrace continuous learning and experimentation to stay updated on emerging technologies, from testing open source tools to engaging in community-building activities like Meetups. Your passion for staying at the forefront of the field will drive your journey.

Data Platform Engineer – Build the Backbone of AICapco at Data & AI Warsaw Tech Summit 2026About Capco Capco drives digital transformation across the financial industry. A global consulting firm focused on financial services, Capco partners with leading banks, fintechs, and financial institutions to design and deliver next-generation data platforms, AI solutions, and digital ecosystems. From data strategy and modern platforms to AI-powered decision systems and GenAI innovation, teams unlock measurable value from data. What defines Capco? A fast, flexible, and entrepreneurial environment. Quick decision-making, creative thinking, and real ownership enable people to push the boundaries of what technology can achieve. Capco stands for: • Trusted partnerships with banks, payments providers, and financial institutions • Delivery of modern data platforms and AI-powered systems • Innovation across cloud, data engineering, machine learning, and GenAI • A community of engineers, architects, and consultants solving complex challenges Meet Capco at the Data & AI Warsaw Tech Summit 🚀At this year’s Data & AI Warsaw Tech Summit, Capco will share how financial institutions can move from experimentation to production-grade AI and scalable data ecosystems. Our experts will explore how organizations can: • Build AI-native architectures on modern cloud platforms • Scale machine learning and generative AI solutions across enterprise environments • Transform fragmented data into high-value data products • Embed AI into real business workflows and decision-making systems Capco Speakers at Data & AI Warsaw Tech Summit 🚀Andrzej Worona & Laura Żusin-KaczmarekTopic: From Data to Meaning: Educating AI in Banking with Ontologies: Lessons from FIBO and Conversational Banking Time: 11:50-12:10 CET Intro: Many AI solutions still fall short when it comes to understanding and reasoning about complex financial concepts. The real challenge is about how financial knowledge is represented and shared with machines. Why does AI still misunderstand basic banking terms despite having access to vast amounts of data? How can AI truly understand financial concepts? Using the Financial Industry Business Ontology (FIBO) as an example of structured domain knowledge, we will discuss how formal, machine-readable definitions can provide the contextual foundation AI needs. By analysing selected conversational banking scenarios and example solutions, we will invite participants to reflect together on what the right semantic layer for AI in banking should look like. Join us to discover why the next leap in AI for banking isn’t just about more data or better models, but about building a structured understanding of financial meaning. Looking for Data Engineers Role OverviewWe are looking for a Data Engineer to join our Data & Analytics team. In this role, you will be responsible for designing, building, and maintaining scalable data pipelines and architectures. You will work closely with data analysts, data scientists, and business stakeholders to ensure reliable and high-quality data is available for decision-making. Key Responsibilities - Design, develop, and maintain ETL/ELT data pipelines - Integrate data from multiple sources (APIs, databases, external systems) - Build and optimize data warehouses and data lakes - Ensure data quality, consistency, and availability - Monitor and improve performance of data processing systems - Collaborate with data scientists and analysts to deliver datasets - Create and maintain technical documentation - Implement and manage cloud-based data solutions (AWS, Azure, GCP) Requirements - Proven experience as a Data Engineer or similar role (3+ years) - Strong SQL skills - Proficiency in Python or Scala - Experience with ETL tools (e.g., Airflow, dbt, Informatica, Talend) - Experience with relational and NoSQL databases - Familiarity with cloud platforms (AWS, Azure, or GCP) - Understanding of data warehousing concepts and data modeling - Experience working with large-scale data (e.g., Spark, Hadoop) - Strong problem-solving and communication skills Nice to Have - Experience with BI tools (e.g., Power BI, Tableau) - Knowledge of DataOps and CI/CD practices - Experience working in Agile environments - Familiarity with Docker and Kubernetes Online Recruitment Process - Screening call with the Recruiter - Hiring Manager Technical Interview - Feedback - Offer We offer a flexible collaboration model based on a B2B contract with the opportunity to work on diverse projects.

• Define and maintain a data engineering roadmap; align technical priorities with business objectives and the Northrop Grumman data strategy • Build and lead a high-performing, collaborative team; mentor engineers on design patterns, code quality, data architecture, and career development • Champion clean, modular architecture and enforce engineering best practices • Drive end-to-end delivery of data pipelines in Databricks, ensuring reliability, scalability, and performance while meeting roadmap milestones • Lead the migration to our Databricks enterprise lakehouse • Collaborate with leaders and teams across various functions

• Develop and maintain integration solutions using MuleSoft and Salesforce-native tools (e.g., Salesforce Flow, Data Loader). • Collaborate with stakeholders, Business Analysts, and development teams to define data models, integration flows, and technical specifications. • Design and implement scalable, secure data architectures aligned with DHS and federal compliance standards (e.g., NIST, FISMA). • Lead data migration efforts from legacy systems to Salesforce, ensuring data integrity, accuracy, and completeness. • Perform data mapping, cleansing, transformation, and validation to support migration and integration workflows. • Write and optimize ETL scripts (e.g., SQL, Apex, Python) for data extraction, transformation, and loading. • Support the Authorization to Operate (ATO) process by contributing to cybersecurity documentation and ensuring compliance with DoD and federal security standards. • Provide technical guidance on data governance, data quality, and integration best practices. • Create and maintain technical documentation, including migration plans, integration specifications, and gate review deliverables. • Participate in Agile ceremonies (e.g., sprint planning, daily stand-ups) to align with team goals and timelines. • Troubleshoot and resolve data or integration issues post-deployment to support ongoing system maintenance.