Senior Data Engineer
Required skills
3 -5 years of experience in the Data Engineering / Data Ops field, ideally working on some big data warehouse projects. You are familiar with the modern data stack and are able to recommend, set up and maintain all different kinds of components from Data ingestion to automation. You have experience with a wide range of tools and technologies within the modern data stack: Kafka, Airflow, Dagster, DBT Core, BigQuery, Lambda functions etc.. You have experience with general infrastructure / DevOps management technologies: ArgoCD, Kubernetes, Docker, Github, Postgres, GCP etc.. You always thrive for applying data engineering best practices: consistency checks, testing data reliability, monitoring on top of ingestion pipelines, no double business logic in the code.
Preferred skills
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Technologies
Kubernetes running on Google Cloud, ArgoCD, Terraform, PostgreSQL, Aiven Kafka Connect, Strimzi, Debezium, DBT cloud, GCP, BigQuery, Fivetran, Go for our API, core logic, and internal tooling, Cypress for automated end-to-end testing, Other odds & ends in JavaScript and shell script.
Responsibilities
Own the data ingestion streams for all of our client’s DBs, from Postgres to BigQuery. Own the overall data infrastructure: set up, maintain and improve our stack with new technologies for more efficiency and best practices. E.g. improve orchestration. Write DWH pipelines and improve our overall DWH code to apply best practices and bring more efficiency. Be part of a data team composed of various profiles, be at the center of all infrastructure decisions and work closely with other stakeholders from the R&D department, especially the DevOps team.
Seniority
Senior
Domain
Data Engineering
