Offer summary

Qualifications:

Proficiency in PySpark and SQL is essential., Experience with cloud computing platforms like AWS or Azure is required., Familiarity with data engineering concepts and data modeling techniques is necessary., Knowledge of tools such as Git, Jenkins, and Code Pipeline is preferred..

Key responsibilities:

Develop and maintain PySpark and Python codes for analytics insights in AWS.

Collaborate with cross-functional teams including Data Engineers, QA Engineers, and DevOps Engineers.

Create data models and design documents based on functional requirements.

Ensure compliance with security policies and stay updated on cloud technologies.

Job description

Must to have skills: Pyspark, SQL, Cloud computing(AWS/Azure or any other cloud)

JOB DESCRIPTION

§ Work with extremely talented peers in a client environment to build new and enhance/maintain existing PySpark, Python codes that generates analytics insights leveraging the big data environment in AWS

§ Proficiency in SQL Writing, SQL Concepts, Data Modelling Techniques & Data Engineering Concepts

§ Experience in working with batch processing / real-time systems using various technologies like Airflow, Databricks, HDFS, Redshift, Hadoop, Elastic MapReduce on AWS

§ Familiar with tools like Git, Code Commit, Jenkins, Code Pipeline

§ Work in a Cross functional team along with other Data Engineers, QA Engineers and DevOps Engineers.

§ Work with Functional Analysts to understand the core functionalities of the solution and build Data Models, Design Documents

§ Develop, test and implement data solutions based on finalized design documents.

§ Ensure adherence with Security and Compliance policies

§ Stay up-to-date with evolving cloud technologies and development best-practices including open-source software.

§ Work in an Agile Environment

Required profile