Data Engineer

Data @ MediBuddy?

Data function at MediBuddy  is designed to Empower all the users to make key decisions using data. We believe in democratizing data so that people can independently explore the data to make informed decisions and derive insights to enhance customer experience at MediBuddy. 

MediBuddy is a matrixed organization which is driven by business and executed by pods and supported by various functions.  Each pod will be working on a specific problem statement which is aligned with the business objective of the specific business unit. The pods are staffed with people from different functional areas. A pod is fundamentally driven by business and executes problems independently of others. 

Tech Stacks: 

1. BI Tool - Superset

2. Databases - Druid, Trino, Redshift, Postgres, MySql, MSSQL

3. Tools -  OpenSearch, Spark, Custom ETL pipeline 

As a Data Engineer, you will play a pivotal role in developing innovative data-driven solutions @MediBuddy.  

What will you do at Medibuddy ?

• Develop, maintain, and run the data platform responsible for ETL (Extract, Transform, Load), dataset management, and data catalog. 

• Maintenance of versioned datasets to enable faster data analytics for product facing features

• Ensuring quality of data, analytics pipeline reliability, and data stack efficiency.

• Drive continuous adoption and integration of relevant and latest technologies into the data platform

• Work and collaborate with cross functional team to deliver the required data sets

What makes you a match for us?

• At least 3+ years of experience as a Data Engineer dealing with large complex data workflows and real-time data pipelines.

• Hands-on experience with Python, SQL, data warehouse design, implementation and maintenance.

• Demonstrated experience in data modeling & ETL development.

• Data Warehousing experience with databases like Redshift, etc.

• Ability to understand basic query profiles and execution plans. Experience in query performance tuning is a plus.

• Coding proficiency in at least one modern programming language (Python, Scala, etc)

• Experience with Big Data Technologies (Presto, Hadoop, Hive, Spark, Airflow, etc.)

• Experience in large-scale data warehousing projects using Redshift, S3, etc.

• Good to have

• Experience with AWS Glue, Airflow, EMR, CDC.

• Experience with data modeling, data warehousing, data lake supporting analytics for BI