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Data Engineer

Norton Blake
City of London
6 days ago
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Data Engineer (Hybrid – London, UK)


Overview


An opportunity for a skilled and motivated Data Engineer to join a growing data engineering team within a fast-paced and innovative environment. This position is ideal for someone who enjoys designing robust, scalable data infrastructure using modern open-source technologies. The role offers exposure to diverse datasets, complex data challenges, and opportunities to influence technical direction and best practices.


Key Responsibilities


  • Design, develop, and maintain data ingestion pipelines using open-source frameworks and tools.
  • Build and optimise ETL/ELT processes for small to large-scale data processing requirements.
  • Develop data models and schemas to support analytics, business intelligence, and product needs.
  • Monitor, troubleshoot, and optimise data pipeline performance and reliability.
  • Collaborate with analysts, engineers, and product teams to gather and translate data requirements.
  • Implement data validation and quality checks to ensure data integrity.
  • Participate in architecture discussions and contribute to technical roadmap planning.


Skills and Attributes


  • Strong analytical mindset with exceptional attention to detail.
  • Excellent problem-solving and debugging skills.
  • Ability to work independently and manage multiple priorities effectively.
  • Clear and confident communication skills, with the ability to explain technical concepts to non-technical stakeholders.
  • Experience working in agile development environments.
  • Passion for continuous learning and staying current with emerging data technologies.


Technical Requirements


  • Proficiency in SQL, including complex query design and optimisation.
  • Strong Python programming skills, particularly with libraries such as pandas, NumPy, and Apache Spark.
  • Experience building and maintaining data ingestion pipelines and optimising performance.
  • Hands-on experience with open-source data frameworks such as Apache Spark, Apache Kafka, or Apache Airflow.
  • Knowledge of distributed computing and big data concepts.
  • Experience using version control systems (Git) and CI/CD practices.
  • Familiarity with relational databases (PostgreSQL, MySQL, or similar).
  • Experience with containerisation technologies (Docker, Kubernetes).
  • Understanding of data orchestration tools (e.g., Airflow or Dagster).
  • Knowledge of data warehousing principles and dimensional modelling.
  • Understanding of cloud platforms and infrastructure-as-code (IaC) practices.
  • Awareness of real-time streaming and data quality monitoring solutions.


Preferred Qualifications


  • Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.
  • 2–5 years of experience in data engineering or similar technical roles.
  • Familiarity with data processes and challenges in the energy or commodities sectors (beneficial but not required).

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