Job Purpose

Responsible for designing, building, and optimizing scalable data infrastructure and pipelines that support the organization's analytics, data science, and AI capabilities. Serves as a senior technical contributor, driving engineering excellence, ensuring reliable and high-performing data solutions, and providing guidance to junior engineers.

Key Result Responsibilities
Design and deliver complex, scalable data pipelines and infrastructure components end-to-end, from requirements through to production
Own the technical design and implementation of data models across relational, NoSQL, and lakehouse architectures to support analytics and ML workloads
Architect and optimize data flows across cloud platforms (Azure, AWS, or GCP), ensuring performance, cost-efficiency, and reliability
Build and maintain robust orchestration workflows using tools such as Apache Airflow, dbt, or Azure Data Factory
Define and implement data quality frameworks — validation rules, automated testing, monitoring, and alerting — across assigned pipeline domains




Collaborate closely with Data Scientists and Analytics Engineers to ensure data infrastructure meets downstream consumption requirements

Key Result Responsibilities-Continued
Contribute to architectural reviews and platform decisions, providing well-reasoned technical input and trade-off analysis
Lead code reviews and enforce engineering best practices, documentation standards, and security and governance requirements
Mentor Associate and mid-level Data Engineers, providing technical guidance and supporting their career development
Proactively identify platform improvements, technical debt, and prospects to modernize the data stack

Qualifications (Academic, training, languages)
Bachelor's or Master's degree in Computer Science, Computer Engineering, Information Technology, or a related field.
Proven experience working with large-scale cloud data platforms in a qualified setting
ITIL

📌 Senior Data Engineer Pune
🏢 Air Arabia
📍 Pune