Urgent Search: Data Engineer II T500-19595

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:

- Builds and maintains relevant and reliable data products that support Finance Analytics. Develops and implements new technology solutions as needed to ensure ongoing improvement with data reliability and observability in-view.
- Participates in new software development and data engineering initiatives supporting Finance Analytics, ensuring timely and accurate delivery of financial data products.
- Drive and implement best Data Engineering practices for pipeline development, data governance, data security and quality across financial datasets.
- Implement security and privacy controls in data workflows, ensuring compliance with finance regulatory requirements.
- Monitor, troubleshoot, and improve performance and reliability of existing finance data pipeline infrastructure.
- Staying up to date with emerging data engineering technologies, trends, and best practices, and evaluating their applicability to meet evolving financial analytics needs.
- Documenting data engineering processes, workflows, and solutions for knowledge sharing and future reference.
- Partner and collaborate with data engineers, particularly in finance-centric data models and processing frameworks.
- Ability and flexibility to coordinate and work with teams distributed across time zones, as needed.

Skill:

- Applies technical data engineering expertise to develop reliable pipelines and improve data quality in support of finance and analytics initiatives
- Bachelor's or master's degree in computer science or related engineering field and deep experience with Cloud computing
- 3+ years of professional experience in data engineering or related fields
- Proficiency in Python, Java, or Scala for data processing and automation
- Hands-on experience with data orchestration tools (e.g., Apache Airflow, Luigi) and big data ecosystems (e.g., Hadoop, Spark, NoSQL)
- Good working knowledge of Data quality functions like cleansing, standardization, parsing, de-duplication, mapping, hierarchy management, etc.
- Ability to perform extensive data analysis (comparing multiple datasets) using a variety of tools
- Effective communication and stakeholder management skills to drive alignment and adoption of data engineering standards
- Demonstrated experience in data management & data governance capabilities
- Familiarity with data warehousing principles and best practices.
- Excellent problem solver - use of data and technology to solve problems or answer complex data related questions
- Excellent collaboration skills to work effectively in cross-functional teams

Work location: Hyderabad, India

Work pattern: Full time role.

Work mode: Hybrid.

---