Senior Data Engineer

As a Senior Data Engineer, you’ll join our data engineering team, working alongside AI engineers, data scientists, backend engineers, analysts, and the BI team.In this crucial role, you will take part in building our next-generation data platform 

You’ll collaborate with different departments to identify data sources that shed light on every aspect of our product, including user behavior, new feature adoption, operational, financial, marketing KPIs, and more.You will work with cutting-edge technologies and address the business needs of other department members, based on an in-depth understanding of our business and landscape.

Responsibilities:

End-to-end development of company data infrastructure

Build and design high-performance, near real-time ETL/ELT processes incorporating current and new data stack tools such as Airflow, AWS, Kubernetes, Databricks, dbt, Spark, and Kafka.

Build and design data platform components to enable clients to produce and consume data

Develop, implement, and maintain change control, testing processes, and monitoring infrastructure

Build and design self-serve components that can speed up the development cycle and time to market

Research and implement best practices and new approaches to our current data stack and systems

Deliver software solutions through iterative and agile processes while maintaining software quality and stability to current systems

Requirements:

5+ years of experience in data engineering or backend engineering roles - a must

Strong knowledge of backend programming languages (Python, Java, Go, Scala, or similar) - a must

Deep knowledge and strong experience deploying distributed data technologies and systems (Spark, Kafka, Airflow, or similar) - a must

Strong and proven knowledge working with data lakes, lakehouses, and data warehouses in the cloud (Databricks, Snowflake, Trino, Cloud Storage, or similar)

Advanced proficiency working with SQL / NoSQL databases

Strong experience with ETL/ELT processes, data ingestion, data transformation, data modeling, and monitoring