Data Engineer

JR United Kingdom; Worcester; On-site; GBP 45,000 - 70,000; Full time

Job summary

A notable organization in data engineering is looking for a Data Engineer to design and implement robust data pipelines. This role requires strong expertise in PySpark and AWS to ensure efficient data management. The ideal candidate will have a solid technical background and be passionate about data-driven innovation. Remote options are available.

Qualifications

• Strong command of PySpark for data processing and AWS for cloud-based solutions.
• Experience in designing and implementing ETL pipeline.
• Solid understanding of Python, PySpark, and SQL.
• Knowledge of Apache Spark and Apache Airflow.
• Experience with AWS services like S3, RDS, Redshift, and Lambda.
• Proficient in using Terraform for AWS resource deployment.
• Experience setting up CI/CD workflows with GitHub Actions.

Responsibilities

• Design and implement data pipelines for efficient data management.
• Ensure integrity and accessibility of data.
• Drive insights for business decisions.

Skills

Proficiency in PySpark and AWS

ETL Pipeline Development

Programming Expertise

Knowledge of Spark and Airflow

Cloud-Native Services

AWS Services

Terraform for Deployment

CI/CD Workflows

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!