Senior Data Engineer

4+ years of relevant experience in API development in Python. Good experience and Proficient in software development lifecycle and software engineering practices. Rich working experience in Pythonic API development frameworks like Flask / FastAPI. Experience in using containerization frameworks like Docker / Kubernetes. Proficiency in understanding of REST APIs, experience in using different types of APIs to either extract data or perform a functionality exposed by APIs. One working in close collaboration with Data Science team is preferred.

You Have

Bachelor’s or master’s degree with 8+ years of experience in Computer Science, Data Science, Engineering, or a related field. 5+ years of experience in API development in Python. Good experience and Proficient in software development lifecycle and software engineering practices. Rich working experience in Pythonic API development frameworks like Flask / FastAPI. Experience in using containerization frameworks like Docker / Kubernetes. Proficiency in understanding of REST APIs, experience in using different types of APIs to either extract data or perform a functionality exposed by APIs.  One working in close collaboration with Data Science team is preferred. 3+ years of experience in developing and maintaining robust data pipelines for both structured and unstructured data to be used by Data Scientists to build ML Models. 3+ years of experience working with Cloud Data Warehousing (Redshift, Snowflake, Databricks SQL or equivalent) platforms and experience in working with distributed frameworks like Spark. 2+ years of hands-on experience in using Databricks platform for data engineering. Detailed knowledge of Delta Lake, Databricks Workflow, Job Clusters, Databricks CLI, Databricks Workspace etc. Hands-on experience in building and maintaining tools and libraries which have been used by multiple teams across organization. e.g. Creating Data Engineering common utility libraries, DQ Libraries etc. Proficient in understanding and incorporating software engineering principles in design & development process. Hands on experience with using CI/CD tools (e.g., Jenkins or equivalent), version control (Github, Bitbucket), Orchestration (Airflow, Prefect or equivalent) Solid understanding of machine learning life cycle, data mining, and ETL techniques. Familiarity with commonly used machine learning libraries (like scikit-learn, xgboost) in terms of exposure and handling of code base which makes use of these libraries for model training & scoring. Excellent communication skills and ability to work and collaborate with cross functional teams across technology and business.

Location:

This position can be based in any of the following locations:

Chennai, Gurgaon

For internal use only:

R000106010