Job Description

About McDonalds in IndiaOne of the worlds largest employers with locations in more than 100 countries McDonalds Corporation has corporate opportunities in Hyderabad. Our global offices serve as dynamic innovation and operations hubs, designed to expand McDonald's global talent base and in-house expertise. Our new office in Hyderabad will bring together knowledge across business, technology, analytics, and AI, accelerating our ability to deliver impactful solutions for the business and our customers across the globe.About McDonalds:One of the worlds largest employers with locations in more than 100 countries, McDonalds Corporation has corporate opportunities in Hyderabad. Our global offices serve as dynamic innovation and operations hubs, designed to expand McDonald's global talent base and in-house expertise. Our new office in Hyderabad will bring together knowledge across business, technology, analytics, and AI, accelerating our ability to deliver impactful solutions for the business and our customers across the globe.Position Summary:Data Quality Engineering Support:(Manager, Data Operations & Management_G4_EDAA0605_EDAA0606_EDAA0607_EDAA0608_EDAA0609)As the Data Quality Engineering Support Manager, you will be responsible for implementing, scaling, and supporting enterprise-wide data quality frameworks across cloud-native data platforms. You will drive hands-on initiatives to monitor, validate, and reconcile data across ingestion, processing, and consumption layersenabling trusted data for analytics, AI/ML, and operational workflows. This role requires a blend of technical depth, platform expertise (e.g., BigQuery, Redshift, GCP, AWS), and collaboration across engineering, governance, and product teams.Who were looking for:Primary Responsibilities:Data Quality Engineering & Monitoring

• Implement and support automated data quality checks for accuracy, completeness, timeliness, and consistency across datasets.
• Develop validation frameworks for ingestion pipelines, curated layers, and reporting models in platforms like BigQuery and Redshift.
• Integrate data quality controls into CI/CD pipelines and orchestration tools (e.g., Airflow, Cloud Composer).

Data Quality Operations

• Respond to and resolve data quality incidents and discrepancies across data domains and systems.
• Collaborate with engineering and product teams to implement root cause analysis and build long-term remediation strategies.
• Establish SLAs and alerting thresholds for data quality KPIs.
• Cloud Platform Integration
• Deploy scalable data quality monitoring solutions across GCP (BigQuery, Cloud Storage) and AWS (Redshift, S3, Glue).
• Leverage platform-native services and third-party tools for automated profiling, rule enforcement, and anomaly detection.

Governance Alignment

• Partner with data governance teams to align quality rules with business glossary terms, reference data, and stewardship models.
• Integrate quality metadata into governance tools such as Collibra, enabling lineage and audit tracking.
• Documentation, Enablement & Collaboration

Maintain playbooks, documentation, and automated reporting for quality audits and exception handling.

• Collaborate with data owners, analysts, and data product teams to promote a culture of data trust and shared ownership.
• Provide training and knowledge-sharing to enable self-service quality monitoring and issue triaging.

Skill:

• 5+ years of experience in data quality engineering, data operations, or data pipeline support, ideally in a cloud-first environment.

Hands-on expertise in:

• Building and managing data quality checks (e.g., null checks, duplicates, data drift, schema mismatches)
• SQL and Python for quality validation and automation
• Working with cloud-native data stacks: BigQuery, Redshift, GCS, S3
• Data quality monitoring tools or frameworks (e.g., Dataplex, Lightup, Collibra)
• Strong troubleshooting skills across distributed data systems and pipelines.
• Bachelors degree in Computer Science, Information Systems, or related field.

Preferred Experience:

• Experience in Retail or Quick Service Restaurant (QSR) environments with high-volume data ingestion and reporting requirements.
• Familiarity with data governance platforms (e.g., Collibra) and integration of quality rules into metadata models.
• Exposure to AI/ML data pipelines and the impact of data quality on model performance.
• Current GCP Associates (or Professional) Certification.

Work location: Hyderabad, IndiaWork hours:Work pattern: Full time role.Work mode: Hybrid.Additional Information:McDonalds is committed to providing qualified individuals with disabilities with reasonable[LG1] accommodations to perform the essential functions of their jobs. McDonalds provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to sex, sex stereotyping, pregnancy (including pregnancy, childbirth, and medical conditions related to pregnancy, childbirth, or breastfeeding), race, color, religion, ancestry or national origin, age, disability status, medical condition, marital status, sexual orientation, gender, gender identity, gender expression, transgender status, protected military or veteran status, citizenship status, genetic information, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.McDonalds Capability Center India Private Limited (McDonalds in India) is a proud equal opportunity employer and is committed to hiring a diverse workforce and sustaining an inclusive culture. At McDonalds in India, employment decisions are based on merit, job requirements, and business needs, and all qualified candidates are considered for employment. McDonalds in India does not discriminate based on race, religion, colour, age, gender, marital status, nationality, ethnic origin, sexual orientation, political affiliation, veteran status, disability status, medical history, parental status, genetic information, or any other basis protected under state or local laws.Nothing in this job posting or description should be construed as an offer or guarantee of employment.

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