Senior Data Engineer

MUST HAVE SNOWFLAKE, AWS,

Salary - £70-80k with 15% bonus

Hybrid working – couple of days in the office

City of London

We are looking for:

• Good understanding of data engineering principles
• A good technical grasp of Snowflake and automating it, and transforming complex datasets
• AWS Skillset
• Delivery experience
• Building solutions in snowflake
• implementing data warehousing solutions using Snowflake and AWS

• Hands-on experience with AWS services such as Glue (Spark), Lambda, Step Functions, ECS, Redshift, and SageMaker.
• Enthusiasm for cross-functional work and adaptability beyond traditional data engineering.
• Examples like building APIs, integrating with microservices, or contributing to backend systems — not just data pipelines or data modelling.
• Mention on tools like GitHub Actions, Jenkins, AWS CDK, CloudFormation, Terraform.

MUST HAVE SNOWFLAKE, AWS

Key Responsibilities:

• Design and implement scalable, secure, and cost-efficient data solutions on AWS, leveraging services such as Glue, Lambda, S3, Redshift, and Step Functions.
• Lead the development of robust data pipelines and analytics platforms, ensuring high availability, performance, and maintainability.
• Demonstrate proficiency in software engineering principles, contributing to the development of reusable libraries, APIs, and infrastructure-as-code components that support the broader data and analytics ecosystem.
• Contribute to the evolution of the team’s data engineering standards and best practices, including documentation, testing, and architectural decisions.
• Develop and maintain data models and data marts that support self-service analytics and enterprise reporting.
• Drive automation and CI/CD practices for data workflows, ensuring reliable deployment and monitoring of data infrastructure.
• Ensure data quality, security, and compliance with internal policies and external regulations.
• Continuously optimize data processing workflows for performance and cost, using observability tools and performance metrics.
• Collaborate cross-functionally with DevOps, analytical engineers, data analysts, and business stakeholders to align data solutions with product and business goals.
• Mentor and support team members through code reviews, pair programming, and knowledge sharing, fostering a culture of continuous learning and engineering excellence.

Skills and Experience:

• Proven experience as a data engineer with strong hands-on programming skills and software engineering fundamentals, with experience building scalable solutions in cloud environments (AWS preferred)
• Extensive experience in AWS services, e.g. EC2, S3, RDS, DynamoDB, Redshift, Lambda, API Gateway
• Solid foundation in software engineering principles, including version control (Git), testing, CI/CD, modular design, and clean code practices. Experience developing reusable components and APIs is a strong plus.
• Advanced SQL skills for complex data queries and transformations
• Proficiency in at least one programming language, with Python strongly preferred for data processing, automation, and pipeline development
• AWS or Snowflake certifications are a plus

• Hands-on experience with AWS services such as Glue (Spark), Lambda, Step Functions, ECS, Redshift, and SageMaker.
• Enthusiasm for cross-functional work and adaptability beyond traditional data engineering.
• Examples like building APIs, integrating with microservices, or contributing to backend systems — not just data pipelines or data modelling.
• Mentions on tools like GitHub Actions, Jenkins, AWS CDK, CloudFormation, Terraform. Personal contribution and not handled by DevOps for candidate's projects

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