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Aberdeen Standard Investments
Data Engineer
Job summary
A leading data solutions company in Maidstone is seeking a detail-oriented Data Engineer to design and implement robust data pipelines. This role is key in ensuring data integrity and accessibility to support critical business decisions. Candidates should have expertise in PySpark, AWS, and ETL development, along with a strong background in Python and SQL. If you’re passionate about data and innovation, we encourage you to apply.
Qualifications
- Strong command of PySpark and AWS for cloud-based solutions.
- Experience in designing, implementing, and debugging ETL pipelines.
- Solid understanding of Python, PySpark, and SQL.
- In-depth knowledge of Apache Spark and Apache Airflow.
- Experience in designing data pipelines with cloud-native services on AWS.
- Knowledge of AWS services such as S3, RDS, Redshift, and Lambda.
- Proficient in deploying AWS resources using Terraform.
- Hands-on experience in setting up CI/CD workflows using GitHub Actions.
Responsibilities
- Design and implement robust data pipelines for efficient data flow.
- Ensure integrity, reliability, and accessibility of data.
- Support critical business decisions and drive insights.
Skills
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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!
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.