Role Description We are seeking a Data Quality Engineer to build and operate the tooling that makes data quality measurable, automated, and continuous. This role builds the instrumentation — automated checks, monitoring, and dashboards that test governed data against rules at scale and surface issues the moment they appear. This is a hands-on engineering role embedded in a lean quality function. You will translate governance rules and quality thresholds into executable tests, integrate them into data pipelines and platforms, and give the organization always-on visibility into the health of its data. You will partner with Governance, Data Operations, and platform teams to embed quality into how data moves rather than checking it after the fact. Responsibilities - Translate authored data rules and quality thresholds into automated, executable quality checks. - Build and maintain data quality monitoring, alerting, and dashboards across governed datasets. - Integrate quality checks into data pipelines, classification workflows, and governance tooling. - Automate detection of rule conflicts, duplicates, and reference data anomalies at scale. - Develop tooling that supports auditors, analysts, and stewards in their day-to-day work. - Instrument human-in-the-loop workflows to capture validation outcomes and quality signals. - Maintain reliable, performant data quality infrastructure and supporting data flows. - Partner with Governance to make rules executable and to close gaps between definition and enforcement. Success in this role will be measured by: - Automated Coverage – Growing share of rules and thresholds enforced by automated checks rather than manual review. - Timeliness – Quality issues surfaced in near-real-time through monitoring and alerting. - Reliability – Stable, performant quality infrastructure and trustworthy metrics. - Enablement – Tooling that measurably improves auditor, analyst, and steward productivity. - Embeddedness – Quality checks integrated into production pipelines and workflows, not bolted on. - Issue Reduction – Measurable decline in quality issues reaching downstream consumers. Qualifications - 4–8 years in data engineering, data quality engineering, analytics engineering, or a related field. - Strong programming skills (e.g., Python, SQL) and experience building data pipelines or automation. - Experience implementing automated data quality checks, testing, or monitoring frameworks. - Familiarity with data quality dimensions and how to operationalize them in code. - Comfort working with cloud data platforms, APIs, and governance/quality tooling. - Ability to translate written rules and standards into executable logic. - Exposure to AI/ML-assisted classification and human-in-the-loop systems a plus. - Strong communication skills and a collaborative, enablement-oriented mindset. Company Description At MediaRadar, we are committed to creating an inclusive and accessible workplace where everyone can thrive. We believe that diversity of backgrounds, perspectives, and experiences makes us stronger and more innovative. We are proud to be an Equal Opportunity Employer and make employment decisions without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, or any other legally protected status. We are also committed to ensuring our recruitment process is accessible to all applicants. If you need a reasonable accommodation during the application or interview process, please contact us at careers@mediaradar.com. We’re excited to meet people who share our values and want to build the future with us.

• Participate in technical interviews (system design + deep dive) • Ask scenario-based questions focused on real production and regulatory challenges • Evaluate candidate answers for practical experience vs. theoretical knowledge • Review take-home tasks or architectural diagrams if applicable • Provide clear, structured written feedback with a hire / no-hire recommendation

Company Description We’re one of the world’s leading online gambling companies, revolutionising the industry since 2000. Founded by Denise Coates CBE, we now employ over 10,000 people and serve over 120 million customers in 26 languages. We empower our employees to push boundaries and explore new ideas, cultivating a culture that celebrates and rewards creativity. This offers employees a wealth of growth opportunities, giving them the opportunity to make a real impact in the world of online gambling. As a forward-thinking company, we’re breaking new ground in software innovation too, redefining what’s possible for our global worldwide. Our focus on In-Play betting has solidified our market-leading position, featuring more than 1.38 million In-Play sporting events a year. With over 750 concurrent sporting fixtures at peak and more live sports streamed than anyone else in Europe (750,000), we handle over 6 million HTTP requests daily and process more than 1.5 million bets per hour at peak. Job Description We are looking for a Data Developer to join the Gaming Platform Team. This team builds the reporting systems that help us meet regulatory requirements in controlled markets. That means working with near real-time and batch data, complex business rules, and changing reporting formats. We are looking for a Data Developer to join the Gaming Platform Team. A crucial requirement of regulated gambling markets is the provision of data to regulators and other third parties. The team is responsible for building and maintaining near real-time and batch reporting systems to fulfil this requirement, with complex business logic to transform internal data models into those required by regulators. The team is creating new GCP reporting systems and will be migrating from on-premise SQL Server systems to Google Cloud Platform, predominantly BigQuery. The successful candidate will contribute to this migration while also developing new cloud-native solutions and exploring AI-driven development and automation to improve efficiency, consistency and reliability across the team's processes. Qualifications - SQL development experience, with the ability to write complex queries, stored procedures, and performance-tune data-intensive workloads. - Experience with Google BigQuery. - Familiarity with GCP services such as Cloud Storage, Cloud Functions, Pub/Sub, or Cloud Composer. - Experience with data pipeline development (ETL/ELT) and orchestration tooling. - Exposure to Infrastructure as Code (e.g. Terraform) and CI/CD pipelines (e.g. Git, GitLab). - Methodical, with high attention to detail and the ability to break down complex requirements into simple solutions. - Real world experience in AI-assisted development tooling (e.g. Claude Code) - Ability to work to deadlines in a fast-paced, reactive environment. - SQL Server experience is beneficial for supporting legacy systems during migration. Additional Information - Develop and maintain regulatory data submission systems, both existing on-premise and new cloud-based solutions in GCP/BigQuery. - Build and maintain automated data pipelines for ingestion, transformation, and loading of regulatory data. - Support the migration of legacy SQL Server solutions to BigQuery, working closely with seniors and technical leads on architecture and data modelling. - Implement data validation, monitoring, and alerting to ensure accuracy, consistency, and reliability of regulatory submissions. - Leverage AI tooling (e.g. Claude Code) and contribute to the team's automation strategies to reduce manual effort and improve quality. - Participate in code reviews and adhere to departmental standards and the development process. - Conduct QA to ensure solutions are accurate, efficient, and performant. - Create and maintain relevant documentation. - Collaborate with other team members to deliver high-quality solutions within required timeframes. By applying to us you are agreeing to share your Personal Data in accordance with our Recruitment Privacy Notice - https://www.bet365careers.com/privacy-policy At bet365, we're committed to creating an environment where everyone feels welcome, respected and valued. Where all individuals can grow and develop, regardless of their background. We're Never Ordinary, and we're always striving to be better. If you need any adjustments or accommodations to the recruitment process, at either application or interview, please don’t hesitate to reach out.

Role Description As a Lead SAP Agent Architect at Parloa, you will help transform customer service with AI agents in enterprise SAP environments. In this customer-facing role, you will support implementations where Parloa’s conversational AI platform must work reliably with SAP data, processes, and integration constraints - from design through testing and go-live readiness. You combine LLM and agent design (prompt engineering, conversational structure, quality, and operational readiness) with hands-on SAP integration literacy: - Understand how Parloa agents should read from and write to SAP systems safely and predictably. - Partner with Forward Deployed Engineering and customer SAP teams to make that path buildable, testable, and production-grade. You will design, prototype, validate, and refine conversational solutions and agent workflows that depend on SAP-backed use cases (for example order management, customer data, case management, and transactional queries), while ensuring the integration layer between Parloa and SAP is reflected accurately in agent behavior, tools, and guardrails. Areas of Ownership - Scope and implement AI Agent deployments, providing strategic advice and execution support to customers and partners with a focus on programs where SAP-backed systems and processes are in scope (for example SAP Service Cloud / CRM, and related enterprise SAP landscapes). - Leverage your knowledge of LLMs (e.g., embeddings) to analyze customer requirements and design precise prompts for reliable, user-aligned behavior, including cases where agent actions depend on SAP-sourced data and SAP business rules. - Simplify complex workflows and processes into digestible conversational components, enabling LLMs to handle challenging tasks effectively. - Fine-tune conversational flows and voice output (e.g., SSML, Lexicons, Regex) to align with customer brand standards. - Build and configure integrations between customers’ systems and Parloa’s platform, connecting external tools (e.g., CRMs, ERPs, ticketing systems, contact center platforms, including SAP CX / SAP ERP surfaces where applicable) via integration platforms and APIs to deliver end-to-end enterprise solutions. - Collaborate with Forward Deployed Engineers on complex or custom integration scenarios that go beyond standard integration capabilities, including SAP-specific connectivity, authentication, and data-access patterns (e.g., OData, REST/SOAP, OAuth2 / SAP IAS / XSUAA) where they materially affect agent behavior and reliability. - Identify and solve blockers together with other departments at Parloa (e.g., Product, Forward Deployed Engineering or Sales) and the customer, including coordination with customer SAP teams and SAP partner engineers when required to unblock delivery. - Apply structured testing approaches to validate AI agent behaviour, quality, and performance under real-world conditions — with explicit coverage for integration-dependent paths common in SAP environments (partial responses, authorization failures, latency, and transactional correctness). - Document best practices, how-to guides, and product capabilities for internal and external audiences, representing the expertise of the Agent Architect team. Qualifications - 4+ years in enterprise customer-facing roles with proven expertise in conversation design and AI agent development for implementation settings (not only concept work). - Exposure to SAP AI Core, SAP Agent Builder, or similar AI extensions within SAP. - Experience with conversational AI / contact center / CX technology in an SAP context. - Demonstrable SAP integration experience in live enterprise delivery contexts, including comfort operating across SAP BTP, S/4HANA, ECC, Service Cloud, CRM, and/or adjacent SAP CX stacks as they relate to agent-connected use cases. - Solid understanding of SAP APIs and data access patterns across one or more relevant surfaces: OData v2/v4, REST/SOAP, and authentication patterns including OAuth2 and SAP IAS/XSUAA. - Strong prompt engineering and LLM workflow design skills: you can analyze requirements and craft prompts/instructions for reliable, user-aligned behavior under enterprise constraints. - Analytical and structured communicator: explicit trade-offs, decisions, next steps; strong stakeholder and milestone discipline. - Proficiency with JSON/XML, API testing tools (e.g. Postman), and reading enterprise API documentation. - Fluency in German and English is required. Nice to Have - Experience working with or for SAP system integrators in delivery or presales-adjacent engineering roles. - Familiarity with cloud landing zones commonly paired with SAP integrations (e.g., Microsoft Azure), Kubernetes concepts, and/or TypeScript/Node.js tooling for integration-heavy delivery. - Git-based collaboration and CI/CD exposure. How You Will Work With Parloa Teams You will work as a technical delivery partner alongside Forward Deployed Engineering (including SAP integration specialists) on shared technical outcomes: reliable connectivity, correct data contracts, and agent behavior that holds up in production. You are expected to work on integration mechanics where they directly impact agent quality: - API contracts, authentication and token flows, request/response shaping, pagination and filtering, error handling, latency and timeouts, and environment-specific constraints. - Debug, validate, and tighten those paths using structured tests and measurable evidence. This is not a “design-only” handoff model: you will configure, test, and iterate integration-connected agent capabilities with the same engineering rigor you apply to prompts and conversational structure, escalating to deeper platform engineering when the problem crosses into core product/runtime ownership. Our Recruiting Process - Talent Acquisition - Hiring Manager - Technical & Expert Interview(s) - Bar Raiser Parloa is committed to upholding the highest data protection standards for our clients' and employees' data. All our employees are instrumental in ensuring the utmost care, GDPR, and ISO compliance, including ISO 27001, in handling sensitive information. Parloa is an e-verify employer in the USA. We provide equal opportunities to all qualified applicants regardless of race, gender, sexual orientation, age, religion, national origin, disability status, socioeconomic background, and other characteristics.