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Data Quality Engineer
Location
India
Posted
3 days ago
Salary
0
Seniority
Mid Level
Job Description
Data Quality Engineer
MediaRadar, Inc.
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.
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bet365At bet365, 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 9,000 people and serve over 100 million customers in 27 languages. Focus on In-Play betting has solidified our market-leading position. Offering an unmatched experience across 96 sports and 700,000 streaming events. Handling over 6 billion HTTP requests daily and processing more than 2 million bets per hour at peak. Empowering employees to push boundaries and explore new ideas. Cultivating a culture that celebrates and rewards creativity. Breaking new ground in software innovation.
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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. 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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. 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