Egen.ai - Data Engineer - Google Cloud Platform (3-13 yrs)

Job Description :

Egen is a fast-growing and entrepreneurial company with a data-first mindset. We bring together the best engineering talent working with the most advanced technology platforms, including Google Cloud and Salesforce, to help clients drive action and impact through data and insights. We are committed to being a place where the best people choose to work so they can apply their engineering and technology expertise to envision what is next for how data and platforms can change the world for the better. We are dedicated to learning, thrive on solving tough problems, and continually innovate to achieve fast, effective results.

As an Egen Data Engineer, you will be responsible for building and implementing distributed ETL/ELT data pipelines to enable the processing of huge data sets, solving ingestion and data modeling challenges at scale, and continuously improving data processing turnaround and usability.

The ideal candidate is very resourceful and has strong production experience working with Python, complex SQL procedures, relational and NoSQL databases, distributed data warehouses, data mapping, data transformations, and data integration.

Responsibilities :

- Design, build and improve scalable and resilient ETL pipelines and integrate with cloud-native data warehouses (Google Cloud) and relational or NoSQL databases.

- Follow and manage best practices and standards for data quality, scalability, reliability, and reusability.

- Debug production issues across data platform services.

- Partner with the business, product, and data science teams to automate processes to improve data sets for analytical and reporting needs.

- Write test cases, perform QA and participate with stakeholders on UAT

Required Experience :

- Bachelor's degree in a relevant field

- Must have strong professional knowledge of and experience building event-driven and/or batch-processed ETL data pipelines

- Enterprise data migration and multi-source ingestion experience

- Proficiency in Python, complex SQL procedure

Nice to have's (but not required) :

- Familiarity with event-driven architecture using Kafka, Airflow, and/or Spark.

- Experience with Docker, Kubernetes.

- Develop and deploy CICD pipelines for Data Engineering