Senior Data Engineer

1 week ago

Cramlington, United Kingdom Printed.com Full time

You will play a crucial role in designing, building, and maintaining our data platform, with a strong emphasis on streaming data, cloud infrastructure, and machine learning operations.

Key Responsibilities:

  • Architect and Implement Data Pipelines:
    • Design, develop, and maintain scalable and efficient data pipelines.
    • Optimize ETL processes to ensure seamless data ingestion, processing, and integration across various systems.
  • Streaming Data Platform Development:
    • Lead the development and maintenance of a real-time data streaming platform using tools like Apache Kafka, Databricks, Kinesis.
    • Ensure the integration of streaming data with batch processing systems for comprehensive data management.
  • Cloud Infrastructure Management:
    • Utilize AWS data engineering services (including S3, Redshift, Glue, Kinesis, Lambda, etc.) to build and manage our data infrastructure.
    • Continuously optimize the platform for performance, scalability, and cost-effectiveness.
  • Communications:
    • Collaborate with cross-functional teams, including data scientists and BI developers, to understand data needs and deliver solutions.
    • Leverage the project management team to coordinate project, requirements, timelines and deliverables, allowing you to concentrate on technical excellence.
  • ML Ops and Advanced Data Engineering:
    • Establish ML Ops practices within the data engineering framework, focusing on automation, monitoring, and optimization of machine learning pipelines.
  • Data Quality and Governance:
    • Implement and maintain data quality frameworks, ensuring the accuracy, consistency, and reliability of data across the platform.
    • Drive data governance initiatives, including data cataloguing, lineage tracking, and adherence to security and compliance standards.

Requirements

Experience:

  • 3+ years of experience in data engineering, with a proven track record in building and maintaining data platforms, preferably on AWS.
  • Strong proficiency in Python, experience in SQL and PostgreSQL. PySpark, Scala or Java is a plus.
  • Familiarity with Databricks and the Delta Lakehouse concept.
  • Experience mentoring or leading junior engineers is highly desirable.

Skills:

  • Deep understanding of cloud-based data architectures and best practices.
  • Proficiency in designing, implementing, and optimizing ETL/ELT workflows.
  • Strong database and data lake management skills.
  • Familiarity with ML Ops practices and tools, with a desire to expand skills in this area.
  • Excellent problem-solving abilities and a collaborative mindset.

Nice to Have:

  • Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
  • Knowledge of machine learning pipelines and their integration with data platforms.

Benefits

  • 22 days holiday Plus 8 days bank holidays
  • Staff discounts & Friends and Family discounts
  • Cycle to work scheme and Tech Scheme
  • Breakfast and drinks provided
  • Charity day per annum supported
  • Summer and Christmas Parties
  • Street food days
  • Perkbox membership
  • Enhanced Maternity & Paternity leave
  • Employee referral scheme

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