Job Purpose
Design and deliver robust, scalable data pipelines and infrastructure components that ensure reliable, high-quality data availability for analytics, data science, and AI workloads. The role operates with growing technical ownership, taking end-to-end responsibility for assigned platform domains and contributing meaningfully to architectural decisions and engineering standards.
Key Result Responsibilities
Design, develop, and maintain scalable ETL/ELT pipelines that ingest, transform, and serve data from structured and unstructured sources across cloud environments
Own assigned pipeline domains end-to-end — from requirements and design through to deployment, monitoring, and iterative improvement
Implement and evolve data models that support analytics, BI, and machine learning consumption requirements
Build and maintain orchestration workflows using tools such as Apache Airflow, dbt, or Azure Data Factory
Optimize pipeline and query performance across cloud data platforms including Snowflake and Azure Synapse
Define and implement data quality rules, automated testing,
and alerting to ensure reliability and consistency of data outputs
Key Result Responsibilities-Continued
Contribute to architectural discussions and platform decisions, providing well-reasoned technical input and trade-off analysis
Collaborate with Data Scientists, Analytics Engineers, and business stakeholders to translate data requirements into maintainable engineering solutions
Conduct code reviews and support the development of Associate and DE I engineers through practical guidance
Maintain explicit documentation for all assigned pipelines, data models, and infrastructure components
Qualifications (Academic, Training, Languages)
Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related field.
Fluent in English Language.
ITIL Certification is an advantage but not mandatory.
Strong proficiency in SQL and Python for data transformation, automation
📌 Data Engineer II (Pune)
🏢 ISA
📍 Pune