Job Description
Job Description
Are You Ready to Make It Happen at Mondelēz International?
Join our Mission to Lead the Future of Snacking. Make It With Pride.
Together with analytics team leaders you will support our business with excellent data models to uncover trends that can drive long-term business results.
How you will contribute
You will:
Work in close partnership with the business leadership team to execute the analytics agenda
Identify and incubate best-in-class external partners to drive delivery on strategic projects
Develop custom models/algorithms to uncover signals/patterns and trends to drive long-term business performance
Execute the business analytics program agenda using a methodical approach that conveys to stakeholders what business analytics will deliver
What you will bring
A desire to drive your future and accelerate your career and the following experience and knowledge:
Using data analysis to make recommendations to senior leaders
Technical experience in roles in best-in-class analytics practices
Experience deploying new analytical approaches in a complex and highly matrixed organization
Savvy in usage of the analytics techniques to create business impacts
The Data COE Software Engineering Capability Tech Lead will be part of Data Engineering and Ingestion team and would be responsible for defining and implementing software engineering best practices, frameworks, and tools that support scalable data ingestion and engineering processes.
This includes building robust backend services and intuitive front-end interfaces to enable self-service, observability, and governance in data pipelines across the enterprise.
Key Responsibilities:
Lead the development of reusable software components, libraries, and frameworks for data ingestion, transformation, and orchestration.
Design and implement intuitive user interfaces (dashboards, developer portals, workflow managers) using React.js and modern frontend technologies.
Develop backend APIs and services to support data engineering tools and platforms.
Define and enforce software engineering standards and practices across the
Data COE for developing and maintaining data product.
Collaborate closely with data engineers, platform engineers, and other COE leads to gather requirements and build fit-for-purpose engineering tools.
Integrate observability and monitoring features into data pipeline tooling.
Lead evaluations and implementations of tools to support continuous integration, testing, deployment, and performance monitoring.
Mentor and support engineering teams in using the frameworks and tools developed.
Qualifications:
Bachelor’s or master’s degree in computer science, Engineering, or related discipline.
12+ years of full-stack software engineering experience, with at least 3 years in data engineering, platform, or infrastructure roles.
Strong expertise in front-end development with React.js and component-based architecture.
Backend development experience in Python with exposure to microservices architecture FAST APIs and RESTful APIs.
Experience working with data engineering tools such as Apache Airflow, Kafka, Spark, Delta Lake, and DBT.
Familiarity with GCP cloud platforms, containerization (Docker, Kubernetes), and DevOps practices.
Strong understanding of CI/CD pipelines, testing frameworks, and software observability.
Ability to work cross-functionally and influence without direct authority.
Preferred Skills:
Proven experience with building internal developer platforms or self-service portals.
Familiarity with data catalogue, metadata, and lineage tools (e.g., Collibra).
Familiarity with Data Quality rules and tolls like Ataccama, Data observability tools like Datadog.
Understanding of data governance and data mesh concepts.
Agile delivery mindset with strong emphasis on automation and reusability.
Tools and Technologies
Frontend Development: React.js
Backend Development: Python, FAST APIs, RESTful APIs, Microservices Architecture.
Cloud Platform: GCP, AWS.
Data warehousing tech: Big Query.
Containerization: Docker, Kubernetes.
CI/CD & DevOps: CI/CD pipelines, Testing Frameworks, Software Observability.
Data Governance: Data catalogue tools (e.g., Collibra), Metadata Management,
Lineage Tools (Collibra), Data Quality tools (Ataccama), Data Observability tools (Datadog), Data Mesh concepts.
Are You Ready to Make It Happen at Mondelēz International?
Join our Mission to Lead the Future of Snacking. Make It With Pride.
Together with analytics team leaders you will support our business with excellent data models to uncover trends that can drive long-term business results.
How you will contribute
You will:
Work in close partnership with the business leadership team to execute the analytics agenda
Identify and incubate best-in-class external partners to drive delivery on strategic projects
Develop custom models/algorithms to uncover signals/patterns and trends to drive long-term business performance
Execute the business analytics program agenda using a methodical approach that conveys to stakeholders what business analytics will deliver
What you will bring
A desire to drive your future and accelerate your career and the following experience and knowledge:
Using data analysis to make recommendations to senior leaders
Technical experience in roles in best-in-class analytics practices
Experience deploying new analytical approaches in a complex and highly matrixed organization
Savvy in usage of the analytics techniques to create business impacts
The Data COE Software Engineering Capability Tech Lead will be part of Data Engineering and Ingestion team and would be responsible for defining and implementing software engineering best practices, frameworks, and tools that support scalable data ingestion and engineering processes.
This includes building robust backend services and intuitive front-end interfaces to enable self-service, observability, and governance in data pipelines across the enterprise.
Key Responsibilities:
Lead the development of reusable software components, libraries, and frameworks for data ingestion, transformation, and orchestration.
Design and implement intuitive user interfaces (dashboards, developer portals, workflow managers) using React.js and modern frontend technologies.
Develop backend APIs and services to support data engineering tools and platforms.
Define and enforce software engineering standards and practices across the
Data COE for developing and maintaining data product.
Collaborate closely with data engineers, platform engineers, and other COE leads to gather requirements and build fit-for-purpose engineering tools.
Integrate observability and monitoring features into data pipeline tooling.
Lead evaluations and implementations of tools to support continuous integration, testing, deployment, and performance monitoring.
Mentor and support engineering teams in using the frameworks and tools developed.
Qualifications:
Bachelor’s or master’s degree in computer science, Engineering, or related discipline.
12+ years of full-stack software engineering experience, with at least 3 years in data engineering, platform, or infrastructure roles.
Strong expertise in front-end development with React.js and component-based architecture.
Backend development experience in Python with exposure to microservices architecture FAST APIs and RESTful APIs.
Experience working with data engineering tools such as Apache Airflow, Kafka, Spark, Delta Lake, and DBT.
Familiarity with GCP cloud platforms, containerization (Docker, Kubernetes), and DevOps practices.
Strong understanding of CI/CD pipelines, testing frameworks, and software observability.
Ability to work cross-functionally and influence without direct authority.
Preferred Skills:
Proven experience with building internal developer platforms or self-service portals.
Familiarity with data catalogue, metadata, and lineage tools (e.g., Collibra).
Familiarity with Data Quality rules and tolls like Ataccama, Data observability tools like Datadog.
Understanding of data governance and data mesh concepts.
Agile delivery mindset with strong emphasis on automation and reusability.
Tools and Technologies
Frontend Development: React.js
Backend Development: Python, FAST APIs, RESTful APIs, Microservices Architecture.
Cloud Platform: GCP, AWS.
Data warehousing tech: Big Query.
Containerization: Docker, Kubernetes.
CI/CD & DevOps: CI/CD pipelines, Testing Frameworks, Software Observability.
Data Governance: Data catalogue tools (e.g., Collibra), Metadata Management,
Lineage Tools (Collibra), Data Quality tools (Ataccama), Data Observability tools (Datadog), Data Mesh concepts.
💡 Quick Summary
Seeking a career-building opportunity? The Software Engineering Capability Lead position is now open for candidates interested in the IT Engineer & Developer Jobs sector. This role in Mumbai offers a professional environment and growth potential.
Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in IT Engineer & Developer Jobs is a plus.
