Senior Data Engineer

Role Overview

• Join a Data Engineering team working on Crypto Secure, a risk assessment platform providing visibility into crypto spend, transaction volumes, and AML risk.

• Design, build, and optimise scalable data platforms that process large, complex financial datasets.

• Work with modern data technologies including Snowflake, Hadoop, Spark, NiFi, and cloud-based data services.

• Play a key role in delivering high-quality data solutions that directly impact fintech and regulatory risk products.

Key Responsibilities

• Build, maintain, and optimise robust data pipelines and ETL workflows for large-scale financial data.

• Implement data architectures based on technical designs and evolving business requirements.

• Write clean, maintainable, production-quality code aligned with engineering best practices.

• Contribute to system design, performance tuning, and optimisation discussions.

• Develop and enforce data quality checks, monitoring, and alerting to ensure reliable data delivery.

• Support metadata management and data governance initiatives.

• Participate actively in agile delivery, including sprint planning, estimation, backlog refinement, and retrospectives.

• Collaborate closely with Product, Data Science, and Software Engineering teams to deliver integrated solutions.

• Support issue triage, troubleshooting, and ongoing reliability of production data systems.

• Mentor junior engineers and contribute to team knowledge sharing and technical standards.

• Continuously learn and apply emerging data engineering tools, techniques, and best practices.

Requirements

• 8+ years of experience in data engineering or a closely related technical role.

• Strong hands-on experience with Snowflake, including performance tuning, security features, and advanced SQL development.

• Expert-level SQL skills, with a proven ability to design and optimise complex queries.

• Solid experience building and optimising data pipelines using big data technologies such as Hadoop, Spark, Databricks, Kafka, and NiFi.

• Proficiency in Python or another object-oriented or functional programming language.

• Experience working with cloud-based data platforms and services.

• Knowledge of stream processing, message queuing, and distributed data processing concepts.

• Experience with data pipeline orchestration and workflow management tools.

• Ability to work with structured and unstructured datasets, extracting insights from complex data sources.

• Familiarity with data governance, metadata management, and data quality frameworks.

• Experience supporting production data systems in fast-paced, high-availability environments.

• Strong understanding of modern software development practices, including version control, testing, and CI/CD.

• Excellent problem-solving and analytical skills with strong attention to detail.

• Proven ability to work independently while collaborating effectively in agile, cross-functional teams.

• Strong communication skills, able to engage with both technical and non-technical stakeholders.