Data Engineer III
McDonald's23 hours ago
Hyderābād, IndiaSenior
Responsibilities
- Build and operate edge-to-cloud streaming and batch ingestion pipelines for restaurant events and equipment telemetry using Confluent Kafka, NATS JetStream, MQTT, Cloud Run, Dataflow, and Pub/Sub.
- Design resilient, idempotent, replayable pipelines that handle late or out-of-order events, duplicates, intermittent connectivity, and schema changes.
- Model time-series and event data in BigQuery and maintain Cloud SQL for PostgreSQL operational stores supporting shift-level APIs.
- Maintain equipment, device, event, restaurant location, and hierarchy reference data.
- Produce feature-ready datasets for computer vision, equipment troubleshooting, quality, and AI agent use cases.
- Serve data and APIs to shift-level operations and restaurant performance applications.
- Manage event schemas and data contracts using Confluent Schema Registry, JSON Schema, CloudEvents, Avro, Protobuf, and Data Interface Contracts.
- Develop orchestration with Apache Airflow and Astronomer, transformations with dbt, and automated testing with Git and GitHub Actions.
- Implement data quality, freshness, latency, alerting, and cost-optimization processes using OpenTelemetry, New Relic, Datadog, and PagerDuty.
- Support restaurant device onboarding and provide level-2 support for production pipeline incidents.
- Use and validate AI-generated code, tests, SQL, dbt models, debugging changes, and documentation with approved AI coding assistants.
- Document pipelines and runbooks, mentor junior engineers, and coordinate with teams across time zones.
Requirements
- 7–11 years of professional experience, including at least 5 years of hands-on data engineering.
- Advanced Python and production-grade SQL skills, including window functions, analytical transformations, and query plan tuning.
- Hands-on experience with Confluent Kafka, Schema Registry, JSON Schema, CloudEvents, and event streaming; Google Cloud Pub/Sub experience is a plus.
- Strong GCP data experience with BigQuery, Cloud Storage, Dataflow or Dataproc, Cloud Run, Cloud SQL for PostgreSQL, Firestore, and IAM.
- Hands-on experience with Apache Airflow, Astronomer, and dbt.
- Experience modeling time-series or event data at scale.
- Practical experience with Docker, Git, GitHub Actions, and Terraform.
- Expertise in data cleansing, standardization, de-duplication, mapping, hierarchy management, and other data quality functions.
- Hands-on experience with AI coding assistants and LLM tools, including responsible handling of confidential and personal data.
- Bachelor’s degree or higher in Computer Science, Engineering, or a related field.
- Preferred experience includes Java, Beam Java SDK, NATS JetStream, MQTT, OpenTelemetry, restaurant equipment data, Tableau or other visualization tools, Vertex AI feature pipelines, and Google Professional Data Engineer certification.
- Additional useful experience includes Scala, dbt Semantic Layer, ontology design, Neo4j, Spanner Graph, Cypher, GQL, SPARQL, and quick-service restaurant or retail operations.
Tech Stack
Categories
Data Engineering
About McDonald's
McDonald’s operates and franchises quick-service restaurants serving burgers, chicken, breakfast items, coffee, and soft drinks to consumers worldwide. The company earns revenue from company-operated restaurants plus franchising fees and real-estate rent paid by independent owner-operators, who run about 95% of its 40,000+ locations across 100+ countries. Founded in 1955 and headquartered in Chicago, it is publicly traded on the NYSE under the ticker MCD.