Burq started with an ambitious mission: to turn the complex process of offering delivery into a simple turnkey solution
Backed by leading venture capitalists, including Village Global
World-class team all over the globe
Responsibilities
Design & Build Pipelines: Develop and maintain scalable ETL/ELT processes to ingest, clean, and transform data from multiple sources (internal systems, third-party APIs, IoT devices)
Data Modeling: Design and implement efficient data models for analytics, machine learning, and operational systems
Infrastructure: Own the data infrastructure, leveraging cloud-native solutions (e.g., AWS, GCP, or Azure) and modern data tools
Collaboration: Partner with data scientists, analysts, and software engineers to deliver data products
Data Quality: Implement robust monitoring, validation, and governance to ensure accuracy, security, and compliance
Scalability: Architect solutions that can handle rapid growth in data volume and complexity
Requirements
Experience: 3+ years of experience in data engineering, preferably in a startup or high-growth environment
Proficiency with SQL and at least one programming language (Python, Scala, or Java)
Experience with cloud data warehouses (Snowflake, BigQuery, or Redshift)
Familiarity with workflow orchestration tools (Airflow, Dagster, Prefect)
Hands-on experience with data streaming (Kafka, Kinesis) is a plus
Mindset: A builder mentality—comfortable with ambiguity, fast iterations, and working in a small but mighty team