Data Engineer (Middle / Strong Middle)
Summary
Data Engineer at DareBay, a UGC marketplace platform connecting brands with content creators, owning and scaling the data infrastructure. Builds batch/streaming ETL/ELT pipelines using Python, advanced SQL, Spark/Flink, Airflow, dbt, Snowflake/BigQuery/Redshift, Kafka, Docker, and Kubernetes.
About Platform DareBay
DareBay is a UGC marketplace platform (Web & Telegram) connecting brands with content creators via automated, metric-based challenges and contests. We are in the pre-release stage - the product is live, scaling fast, and you will see the direct impact of your work immediately.
The Role
We are looking for a Data Engineer (2–4 years of exp.) to own, audit, and scale our data infrastructure. You will maintain data platforms under growing client loads, working closely with the CTO, Backend team, and Data Analysts.
Key Responsibilities:
Audit, optimize, and maintain the existing data infrastructure.
Build and scale reliable batch/streaming ETL/ELT pipelines.
Collaborate with the CTO and analytics team to ensure data availability and quality.
Technical Stack:
Core: Python & Advanced SQL (optimization, window functions).
Processing & Orchestration: Apache Spark / Flink, dbt, Apache Airflow.
DWH & Lakes: Snowflake / BigQuery / Redshift, ClickHouse (OLAP), Apache Iceberg.
Streaming & Infra: Apache Kafka, Docker, Kubernetes, CI/CD.
Data Quality: Great Expectations / Soda / Monte Carlo.
Pluses: Java, Grafana/Prometheus, Telegram Bot API.
Requirements:
2–4 years of commercial Data Engineering experience.
English: Upper-Intermediate (for documentation and tech communication).
Ability to work closely with cross-functional teams (CTO, Backend, Analytics).
What We Offer:
Remote-first format & flexible hours.
Direct impact on architecture at an early scaling stage.
Direct collaboration with the core team (CTO).