Cloud Data Engineer

Overview

We are seeking a talented and motivated AWS Cloud Data Engineer to join our growing engineering team. In this role, you will be responsible for designing, building, and maintaining cloud-based data infrastructure and pipelines that enable the efficient ingestion, storage, and analysis of large datasets. You will work closely with cross-functional teams including data architects, data analysts, systems and software engineers to optimize data workflows and deliver high-quality data solutions for continuous infrastructure compliance.

Location: 2 days per week in Canary Wharf, London

Responsibilities:

• Understand and implement data fabric principles and methodologies to enhance data ingestion and processing.
• Develop scalable and resilient cloud-based data architectures/ data lakes/data warehousing solutions and pipelines that meet the needs of both structured and unstructured data.
• Ensure data is available, consistent, and optimized across all stages from ingestion to consumption. Work with multiple small to large datasets, performing ETL or ELT processes (where required).
• Utilize cloud platforms (primarily AWS) to deploy data solutions that leverage native services such as S3, Lambda, Redshift, Glue, Airflow, or equivalent third party SAAS services like Snowflake etc for data lake/data warehousing patterns.
• Continuously monitor and optimize the performance, cost, and scalability of data infrastructure and pipelines.
• Implement best practices for data security and compliance, including encryption, data masking, and auditing across all data processes.
• Work closely with data and product analysts, and software development teams to ensure data availability and quality for business insights and machine learning models.
• Leverage automation tools and scripts to reduce manual effort and ensure repeatability of data workflows.
• Maintain clear and detailed documentation of all data architectures, processes, and workflows.
• Integrate AWS native scanning capabilities with internal security standards, ensuring compliance and security.
• Design, implement, and manage data pipelines using cloud native or third party services.

Qualifications & Experience:

• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• 8+ years of experience in data engineering or a related field within the financial services industry.
• Strong understanding of data lake principles, data governance, data quality, and data security best practices.
• Proven experience with AWS cloud platforms on data storage, processing, management and capturing Data analytics and insights
• Hands-on experience with ETL tools and processes, and orchestration platforms such as Apache Airflow or AWS Step Functions with data pipeline tools like Airflow/Databricks.
• Proven experience with AWS data services, including S3, Glue, Redshift, RDS, DynamoDB, Lambda, and Athena.
• Strong understanding of relational databases, NoSQL databases, and data warehousing.
• Expertise in SQL, Python, and distributed data systems
• Deep expertise in Infrastructure As Code (IaC) principles and best practices.
• Proficiency with IT tooling and automation products, including Chef Inspec, Ansible/Ansible tower, SNOW, and JIRA.
• Experience designing and managing CI/CD or data pipelines.
• Ability to troubleshoot complex issues in cloud environments and ensure optimal performance of data systems.
• Strong communication and collaboration skills, with the ability to work effectively in an Agile team environment and contribute to the design and scrum meetings.

Why Join Bell

• We prioritise internal development opportunities and offer access to our Udemy training platform
• Competitive Salary
• Flexible remote working and a supportive environment for varying personal circumstances
• A diverse and inclusive work culture
• Modern vibrant workplaces
• Company pension
• Private healthcare/dental care
• Cycle to work scheme
• And much more!

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