Engineering

Data Engineer

Cambourne
Work Type: Full Time
Required Qualifications & Skills – Senior Data Engineer
We are seeking an experienced Senior Data Engineer to design, build, and maintain scalable data pipelines and distributed data processing solutions.

Mandatory / Primary Skills:
Python
PySpark
AWS
SQL

Experience
  • 4 to 7 years of hands-on experience in Data Engineering and building scalable data solutions.
  • Strong experience working with AWS-based data engineering services and cloud data platforms.
Technical Skills
  • Strong hands-on expertise in Python and PySpark for large-scale data processing.
  • Advanced proficiency in SQL, including writing complex queries, query optimization, and data analysis.
  • Strong experience with AWS services relevant to data engineering and cloud-based data processing.
  • Strong understanding of Apache Spark and distributed data processing systems.
  • Experience designing, developing, and maintaining scalable and high-performance ETL/ELT data pipelines.
  • Experience in data ingestion, transformation, integration, and processing from multiple data sources.
  • Experience working with structured, semi-structured, and unstructured data such as JSON, logs, PDFs, and other file formats.
  • Strong knowledge of relational and non-relational databases.
  • Experience in data quality checks, validation, performance tuning, and optimization.
Analytical & Problem-Solving Skills
  • Strong ability to perform deep-dive data analysis and troubleshoot complex data-related issues.
  • Proven experience in building scalable data solutions to address complex business requirements.
  • Strong problem-solving and analytical skills.
Soft Skills
  • Strong verbal and written communication skills.
  • Good organisational and stakeholder-management skills.
  • Proactive self-starter with the ability to work independently and take ownership.
Technical Agility
  • Ability to adapt quickly to new technologies and data platforms.
  • Passion for staying current with emerging trends and best practices in Data Engineering, AWS, and Big Data technologies.

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