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Data Engineer
JR United Kingdom
Peterborough
Teletrabalho
GBP 50.000 - 70.000
Tempo integral
Há 30+ dias

Resumo da oferta

A leading technology company in the UK is seeking a proactive Data Engineer to design and implement robust data pipelines. The ideal candidate will have experience with PySpark, AWS, and ETL development. This role is crucial for ensuring data integrity and supporting business decisions through efficient data management. If you're passionate about data and innovation, we encourage you to apply.

Qualificações

  • Strong command of PySpark and AWS for data processing and cloud solutions.
  • Experience in designing and implementing ETL pipelines.
  • Solid understanding of Python, PySpark, and SQL.

Responsabilidades

  • Design and implement data pipelines for efficient data flow.
  • Ensure integrity and reliability of data across platforms.
  • Work with cloud-native services to enhance data management.

Conhecimentos

Proficiency in PySpark
AWS expertise
ETL Pipeline Development
Programming in Python
Knowledge of Spark
Knowledge of Airflow
Cloud-Native Services
Terraform for Deployment
CI/CD Workflows

Ferramentas

SQL
AWS Services (S3, RDS, Redshift, Lambda)
Descrição da oferta de emprego

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London Remote

**About the Role**

The Data Engineer will play a pivotal role in organization by designing and implementing robust data pipelines that facilitate efficient data flow and management across various platforms. This position is essential for ensuring the integrity, reliability, and accessibility of our data, which supports critical business decisions and drives insights.

**Required Skills**

- **Proficiency in PySpark and AWS:** You should have a strong command of both PySpark for data processing and AWS (Amazon Web Services) for cloud-based solutions.

- **ETL Pipeline Development:** Demonstrated experience in designing, implementing, and debugging ETL (Extract, Transform, Load) pipelines is crucial. You will be responsible for moving and transforming data from various sources to data warehouses.

- **Programming Expertise:** A solid understanding of Python, PySpark, and SQL is required to manipulate and analyze data efficiently.

- **Knowledge of Spark and Airflow:** In-depth knowledge of Apache Spark for big data processing and Apache Airflow for orchestrating complex workflows is essential for managing data pipelines.

- **Cloud-Native Services:** Experience in designing data pipelines leveraging cloud-native services on AWS to ensure scalability and reliability in data handling.

- **AWS Services:** Extensive knowledge of various AWS services, such as S3, RDS, Redshift, and Lambda, will be necessary for building and managing our data infrastructure.

- **Terraform for Deployment:** Proficient in deploying AWS resources using Terraform, ensuring that infrastructure as code is implemented effectively.

- **CI/CD Workflows:** Hands-on experience in setting up Continuous Integration and Continuous Deployment (CI/CD) workflows using GitHub Actions to automate the deployment process and enhance collaboration within the team.

**Preferred Skills**

- **Experience with Other Cloud Platforms:** Familiarity with additional cloud platforms, such as Google Cloud Platform (GCP) or Microsoft Azure, will be advantageous and broaden your impact within our data architecture.

- **Data Governance and Compliance:** Understanding of data governance frameworks and compliance standards will be beneficial as we prioritize data privacy and regulatory requirements.

We are looking for a proactive and detail-oriented Data Engineer who is passionate about working with data and driving innovation . If you have a strong technical background and a commitment to excellence, we would love to hear from you!

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* O salário de referência é obtido com base em objetivos de salário para líderes de mercado de cada segmento de setor. Serve como orientação para ajudar os utilizadores Premium na avaliação de ofertas de emprego e na negociação de salários. O salário de referência não é indicado diretamente pela empresa e pode ser significativamente superior ou inferior.

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