Engineer - Data Engineer

Accountabilities

Architect of Solutions: Lead the design, development, and enhancement of scalable ETL pipelines and Data Products, as part of a Data Mesh inspired strategy.

Technical Expertise: Demonstrate your expertise in ELT solutions (DBT, Snowflake), Python and AWS ecosystems to deliver exceptional solutions.

Collaborative Spirit: Work hand-in-hand with global and diverse Agile teams, from data to design, to overcome technical data challenges.

Innovate & Inspire: Stay ahead of the curve by integrating the latest industry trends and innovations into your work such as GenAI.

Tools:

ETL Tools: Master tools like Python and explore preferred technologies such as DBT and Snowflake.

Databases: Utilize your SQL prowess across platforms like Snowflake, Postgres.

AWS Cloud Expertise: Bring your AWS knowledge to life with services like Lambda, S3, Athena, Step Functions and more.

Essential Skills/Experience

1. 3 to 6 years’ experience
2. A proactive mindset and enthusiasm for Agile environments.
3. Strong hands-on experience with cloud providers and services.
4. Experience in performance tuning SQL and ETL pipelines.
5. Extensive experience in troubleshooting data issues, analyzing end-to-end data pipelines and in working with users in resolving issues.
6. Masterful debugging and testing skills to ensure excellence in execution.
7. Inspiring communication abilities that elevate team collaboration.
8. Experience of structured, semi-structured (XML, JSON) and unstructured data handling including extraction and ingestion via web-scraping and FTP/SFTP.
9. Production experience delivering CI/CD pipelines (Github, Jenkins, DataOps.Live).
10. Excellent Cloud Devops Engineer who can develop, test and maintain CICD Pipeline using Terraform, cloud formation.
11. Remain up to date with latest technologies, like GenAI / AI platforms and FAIR scoring to improve outcomes