Position: Data Engineer (experience building data lake in AWS)
Company: Akvelon
Category: Data Engineer
Experience required: 5y
English level: intermediate

The Akvelon is looking for a forward-thinking technically savvy Data Engineer to help build Data Lake for building insights and predictability on customer. 

The suitable person will be allowed to bring innovative ways to solve problems for the next generation of the news organization

1.	Build and manage Data Lake in AWS using AWS native services from scratch.
2.	Strong communication skills and is a thought leader - Ability to clearly articulate technical vision and technological considerations.
3.	Real-world solid experience building data lake in AWS 
4.	Good understanding of the different design patterns for a data lake and how to build things from the ground up.
5.	Experience with some of the following skills and technologies:
•	Batch & streaming data pipelines (Spark, Beam, Kafka, Kinesis etc.)
•	Workflow orchestration (Airflow, Dagster, Luigi, etc)
•	Data quality monitoring & observability
•	Data modeling (SQL, dbt, Spark)
•	REST, GraphQL & SOAP APIs
•	Data security & compliance (encryption, data masking, SSH tunnels, etc)
•	Experience in using Python for Data processing.

Working conditions and benefits:
🔸Paid vacation, sick leave
🔸Official state holidays
🔸Professional growth while attending challenging projects and the possibility to switch your role, master new technologies and skills with company support
🔸Flexible working schedule: 8 hours per day, 40 hours per week. It additionally depends on the project operational hours. Work on weekends or overtime is only upon request of the customer, and is paid in addition
🔸Personal Career Development Plan (CDP)
🔸Employee support program (Discount, Care, Heals, Legal compensation)
🔸Paid external training, conferences, and professional certification that meets the company’s business goals
🔸Internal workshops & seminars
🔸Corporate library (Paper/E-books) and internal English classes