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hibob

Senior Data Engineer

Bamboo Card
Dubai, UAE
Full-time
Senior · 5+ years experience
Onsite
Discovered 2 weeks ago
SQLSnowflakeBigQueryRedshiftdbtAirflow
Free

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SQLSnowflakeBigQuery
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Job requirements

  • Build the Foundation: Architect, build, and scale our modern data stack from the ground up, starting with our first centralized data warehouse.
  • Pipeline Engineering: Design and develop robust, scalable ETL/ELT pipelines to ingest data from various internal and external sources.
  • Data Modeling & Governance: Establish clean, reliable data models and ensure data quality, integrity, and documentation across the board.
  • Analytics & Visualization: Design and build intuitive Power BI dashboards that provide actionable insights to business leaders and stakeholders.
  • Predictive Capabilities: Leverage AI-driven analytics and machine learning tools to unlock advanced forecasting capabilities and predictive insights.
  • Strategic Partnership: Collaborate directly with leadership and cross-functional teams to understand their data needs and translate them into technical solutions.

Job responsibilities

  • You thrive in ambiguity: You are comfortable being the sole expert in the room when it comes to data. You don't need a playbook - you write it.
  • You are a practical builder: You know how to balance "perfect architecture" with "getting things done." You prefer building high-impact MVPs over over-engineering.
  • You have a product mindset: You don’t just build pipelines; you care about how the end-users (business teams) interact with the data.

Job benefits

  • 5+ years of experience in data engineering. Experience as an early data hire at a startup is a massive plus.
  • Strong proficiency in SQL, and modern data warehousing tools (e.g., Snowflake, BigQuery, Redshift).
  • Experience with ETL/ELT tools (e.g., dbt, Airflow, Fivetran, or custom scripts).
  • Deep, hands-on experience building, optimizing, and maintaining Power BI dashboards.
  • Exposure to or experience implementing AI/ML models for business forecasting and predictive analytics.
  • Nice to Haves: Experience with AWS ecosystem (Aurora, RDS, Glue), Experience with financial or transactional datasets.

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