Software Engineering Capability Lead

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 Capabilit y 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: - bachelors or masters 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 e xperience with building internal developer platforms or self-service portals. - Familiarity with data catalogue , metadata, and lineage tools (eg, 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 (eg, Collibra), Metadata Management, - Lineage Tools (Collibra) , Data Quality tools ( Ataccama ), Data Observability tools (Datadog), Data Mesh concepts. Optional Skills - Data Engineering Tools: DBT, Apache Airflow , data bricks. - Familiarity with SSO tools like PingID Skills: Gcp, Restful Apis, react.js , Python Experience: 12.00-15.00 Years