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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 Data Engineer who has a good 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 Data Engineer, you will collaborate with data scientists, analysts, and other cross-functional teams to ensure the availability, reliability, and performance of data systems. Vital team member for 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 are looking for:
Primary Responsibilities:
Skill:
Work location: Hyderabad, India
Work pattern: Full time role.
Work mode: Hybrid.
Job ID: 148999017
Skills:
Java, Cloud Computing, Data Management, Scala, Data Governance, Python, Data warehousing principles
Skills:
Coding, Data Engineer, Spark, Loans
Skills:
graph databases , object storage , Java, AWS Glue, Data Modeling, Sql, ELT, Python, Etl, column-family databases, key-value stores, IAM roles and permissions, non-relational databases
Skills:
S3, Data Modeling, AWS Glue, Emr, Redshift, Sql, Lambda, Kinesis, Python, Unix Shell Scripting, Etl, AWS, FireHose, IAM roles and permissions
Skills:
Git, Power Bi, Data Warehousing, Apache Spark, Databricks, Data Modeling, Api Integration, Sql, Python, ETL processes, Medallion Architecture
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