Data Engineer

JR United Kingdom; Wakefield; On-site; GBP 50,000 - 70,000; Full time

Job summary

A leading data solutions provider is seeking a Data Engineer to design and implement robust data pipelines. The ideal candidate will have strong skills in PySpark and AWS, experience with ETL development, and a solid grasp of CI/CD workflows. This role is pivotal for ensuring data integrity and driving insights for critical business decisions. If you are passionate about data and innovation, we would love to hear from you!

Qualifications

• Strong command of PySpark for data processing and AWS for cloud-based solutions.
• Experience in designing and debugging ETL pipelines.
• Solid understanding of data manipulation using Python, PySpark, and SQL.
• Knowledge of Apache Spark for big data processing and Apache Airflow for workflows.
• Familiar with AWS services like S3, RDS, Redshift, and Lambda.
• Proficient in deploying with Terraform and implementing CI/CD workflows.

Responsibilities

• Design and implement data pipelines for efficient data flow.
• Ensure integrity, reliability, and accessibility of data.
• Collaborate on enhancing data infrastructure with cloud-native services.

Skills

PySpark

AWS

ETL Pipeline Development

Python

SQL

Apache Spark

Apache Airflow

Terraform

CI/CD Workflows

Tools

AWS S3

AWS RDS

AWS Redshift

AWS Lambda

GitHub Actions

Job description

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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!