The idea of DataZymes germinated with the realization that Pharma Commercial teams had few alternatives to the antiquated and inefficient solutions offered by traditional consulting and technology companies. Already a laggard in analytical maturity, the Pharma industry had been facing challenges to adapt to a Big Data world.

We saw that the products offered by technology companies were too rigid and generic to handle novel problems. The custom solutions offered by consulting organizations took too long to deploy and required many services to maintain and improve.

We felt the need for a different approach to finding solutions and we knew it would take a different kind of company to build it. That's why DataZymes.

We're focused on creating the world's best user experience for working with data, one that empowers people to ask and answer complex questions without requiring them to master querying languages, statistical modeling, or the command line. To achieve this, we are building platforms for integrating, managing, and securing data on top of which we layer applications for fully interactive machine-driven, human-assisted analysis.

Responsibilities :

- Design and implement data pipelines using AWS services such as S3, Glue, PySpark and EMR.

- Develop and maintain data processing and transformation scripts using Python and SQL.

- Optimize data storage and retrieval using AWS database services such as RDS, Redshift and DynamoDB.

- Build different types of data warehousing layers based on specific use cases.

- Utilize expertise in SQL and have a strong understanding of ETL and data modelling.

- Ensure the accuracy and availability of data to customers and understand how technical decisions can impact their businesss analytics and reporting.

- Experience with AWS cloud and AWS services such as S3 Buckets, Glue Studio, Redshift, Athena, Lambda, and SQS queues

Qualifications :

- Bachelors or masters degree in computer science, Information Technology

- Experience with batch job scheduling and identifying data/job dependencies.

Preferred Skills :

- Proficiency in data warehousing, ETL, and big data processing.

- Familiarity with the Pharma domain is a plus.