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About McDonald's:
One of the world's largest employers with locations in more than 100 countries, McDonald's 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:
Looking to hire a Senior Engineer at the G5 level who has a deep understanding of Data Product Lifecycle, Standards and Practices. Will be responsible for building scalable and efficient data solutions to support the Finance, Franchising & Development function with a specific focus on the Finance Analytics product and initiatives. As a Senior Engineer, you will collaborate with data scientists, analysts, and other cross-functional teams to ensure the availability, reliability, and performance of data systems. Leads initiatives to enable trusted financial data, supports decision-making, and partners with business and technology teams to align data capabilities with strategic finance objectives. Expertise in cloud computing platforms, technologies and data engineering best practices will play a crucial role within this domain.
Who we're looking for:
Primary Responsibilities:
Skill:
Work location: Hyderabad, India
Work pattern: Full time role.
Work mode: Hybrid.
Job ID: 149211397
Skills:
data masking , Paas, Github, Adf, ADO, Azure Synapse, Encryption, Sonarqube, Azure Data Lake, Ml, Migrations, Power Bi, Azure Sql, DevSecOps, GenAI, Azure stack, SRE, Safe, FaaS, compliance standards, Lakehouse Medallion Architecture, Distributed database architectures, Datawarehouse modeling techniques, Data Platform Modernization, Lean, Ai, Security Governance, cloud-native engineering, microservices architecture, Xp, data governance frameworks
Skills:
Distributed Systems, Data Architecture, Software development best practices, Data engineering best practices, Data pipelines, Data Product Lifecycle Standards and Practices
Skills:
Information Architecture, Data Science, Agile, automation, enterprise data platforms, Continuous Improvement, AI analytics, digital enablement, Lean Six Sigma
Skills:
data engineering , snowflake , Data Modeling, Data Architecture, Python, Sql, ELT, Etl, Cortex AI, Claude, Matillion
Skills:
Cloud Technologies, AWS, enterprise software delivery, post-trade lifecycle management, index data processing pipelines, trading workflows, SDLC methodologies, market data flows, Trade Processing, financial data platforms, Settlement, trading systems, Oracle-based data ecosystems, IT project planning, Reconciliation, middle and back-office technology platforms
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