Data Engineer II [T500-19595]

McDonald's

Hyderabad

On-site

INR 800,000 - 1,200,000

Full time

14 days+

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Job summary

A leading global fast-food company in Hyderabad seeks a Data Engineer to build scalable data solutions supporting finance analytics. The role requires expertise in data pipeline development, cloud computing, and programming languages such as Python or Java. The ideal candidate will have a bachelor's or master's degree and at least 3 years of relevant experience. This full-time role promises an engaging work environment focused on innovative financial analytics.

Qualifications

Deep experience in cloud computing.
3+ years of professional experience in data engineering or related fields.
Familiarity with data warehousing principles.

Responsibilities

Build and maintain reliable data products supporting Finance Analytics.
Develop technology solutions to improve data reliability and observability.
Ensure compliance with finance regulatory requirements.

Skills

Data pipeline development

Data quality improvement

Python programming

Java programming

Data orchestration tools

Problem-solving

Education

Bachelor's or master's degree in computer science or related field

Tools

Apache Airflow

Hadoop

Spark

Job description

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:

We are looking to hire a Data Engineer with a good understanding of Data Product Lifecycle, Standards, and Practices. The role involves building scalable and efficient data solutions to support the Finance, Franchising & Development functions, focusing on Finance Analytics products and initiatives. The Data Engineer will collaborate with data scientists, analysts, and cross-functional teams to ensure data systems' availability, reliability, and performance. This role is vital for enabling trusted financial data, supporting decision-making, and aligning data capabilities with strategic finance objectives. Expertise in cloud platforms, technologies, and data engineering best practices is essential.

Key Responsibilities:

Build and maintain reliable data products supporting Finance Analytics.
Develop and implement technology solutions to improve data reliability and observability.
Participate in software development and data engineering initiatives for Finance Analytics, ensuring timely delivery.
Implement best practices for data pipelines, governance, security, and quality across financial datasets.
Ensure compliance with finance regulatory requirements through security and privacy controls.
Monitor and troubleshoot data pipeline performance and reliability.
Stay updated on emerging data engineering trends and evaluate their applicability.
Document processes and workflows for knowledge sharing.
Collaborate with finance-focused data engineering teams.
Coordinate with distributed teams across time zones as needed.

Skills and Qualifications:

Technical expertise in developing reliable data pipelines and improving data quality for finance and analytics.
Bachelor's or master's degree in computer science or related field, with deep experience in cloud computing.
3+ years of professional experience in data engineering or related fields.
Proficiency in Python, Java, or Scala for data processing and automation.
Experience with data orchestration tools (e.g., Apache Airflow, Luigi) and big data ecosystems (Hadoop, Spark, NoSQL).
Knowledge of data quality functions such as cleansing, standardization, parsing, de-duplication, and hierarchy management.
Ability to perform extensive data analysis using various tools.
Strong communication and stakeholder management skills.
Experience in data management and governance.
Familiarity with data warehousing principles and best practices.
Excellent problem-solving skills and collaboration abilities.

Work Pattern: Full-time role.

Seniority Level