Data Engineer Lead


Singapore
Permanent
Negotiable
Quantitative Analytics Research and Trading
PR/578250_1774231089
Data Engineer Lead

Responsibilities

  • Design, build, and scale modern data platforms (data lakes, warehouses, lakehouse architectures)

  • Develop and maintain robust ETL/ELT pipelines across batch and real-time data sources

  • Enable AI/ML and GenAI use cases by building data pipelines, feature stores, and supporting model productionization

  • Remain hands-on in coding (Python, SQL, Spark), architecture design, and troubleshooting complex data issues

  • Architect and manage cloud-based data platforms (AWS, Azure, or GCP) using modern tools (e.g., Databricks, Airflow, Kafka, dbt)

  • Lead and mentor a team of data engineers, setting technical standards and best practices

  • Collaborate with cross-functional teams (AI, product, business) to translate requirements into scalable data solutions

  • Establish data governance, lineage, security, and ensure compliance with regulatory standards

Requirements

  • 8-12+ years of experience in data engineering, with a proven track record of building and scaling production-grade data platforms

  • Strong hands-on experience in Python, SQL, and distributed data processing frameworks (e.g., Spark)

  • Experience with cloud platforms (AWS, Azure, or GCP) and modern data stack tools (Databricks, Airflow, Kafka, dbt)

  • Exposure to AI/ML workflows and familiarity with GenAI concepts (e.g., LLMs, RAG pipelines)

  • Proven experience leading teams while remaining hands-on in technical delivery

  • Strong understanding of data architecture, data modeling, and data governance frameworks

  • Excellent problem-solving skills and ability to operate in a fast-paced, evolving environment

  • Strong communication skills with the ability to engage both technical and non-technical stakeholders

FAQs

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