Data platform engineer in fintech

The Senior Data Platform Engineer is a technical leader who empowers data, analytics and product teams across Pepperstone by building and operating the Enterprise Data Platform, ensuring it meets the demanding requirements of high-frequency trading environments and regulatory compliance in financial markets. This role is hands-on across our modern AWS-native stack: real-time change data capture with Debezium, event streaming on Kafka (MSK), stream processing with Apache Flink, cloud data warehousing on Snowflake, integration to Alation, all delivered through Terraform, GitHub and GitHub Actions using infrastructure-as-code and CI/CD best practice.

• Work with the Data Platform team to design, implement and maintain scalable, secure and resilient services across the Pepperstone Enterprise Data Platform
• Own and operate core streaming infrastructure — Debezium (CDC), Kafka (MSK), and Apache Flink — ensuring reliability, performance, and availability for consuming teams
• Optimise critical Data platform services including data lakes, data warehouses, stream processing (Kafka, Flink), and real-time analytics platforms on AWS
• Design, provision, and manage cloud infrastructure using Terraform — including Snowflake environments, AWS data services, networking, IAM, and supporting services, with a self-service platform provisioning mindset
• Implement and enforce AWS resource tagging strategies, cost allocation policies, and FinOps practices to drive cloud cost transparency and optimisation across the EDP
• Drive technical initiatives from conception to delivery, managing stakeholder expectations and coordinating cross-functional efforts with both technical and business teams
• Design and implement sophisticated monitoring, alerting, and observability solutions for data platform services, leading incident response and post-mortem analysis
• Collaborate closely with the data governance team to design and implement robust governance frameworks, including Snowflake data sharing, masking policies, and row-level security
• Integrate AI-assisted tooling and Model Context Protocol (MCP) capabilities into data platform workflows to enhance developer productivity and data discoverability
• Assist the Data Platform Lead in evaluating and integrating third-party vendors and technologies, conducting proof-of-concepts and making build-vs-buy recommendations based on technical and business criteria
• Stay at the forefront of industry trends, emerging technologies, and market changes in data platforms, cloud services, and the broader fintech landscape.

• Bachelor's degree in computer science, engineering, or equivalent extensive professional experience in data platform engineering
• Minimum 5 years' experience in a data platform, data engineering, cloud or DevOps role, with at least 3 years building production workloads on AWS
• Strong hands-on experience with infrastructure-as-code tooling for managing cloud and data infrastructure, including module design, state management, and multi-environment promotion
• Proficient with source control and CI/CD practices; comfortable designing reusable pipelines and enforcing quality gates
• Production experience with event streaming and stream processing platforms, including operational tuning and resilience patterns
• Hands-on experience with cloud data warehousing platforms, including architecture, performance optimisation, and governance features
• Solid understanding of core cloud services relevant to data platforms: compute, storage, networking, IAM, managed databases, secrets management, and observability.
• Ability to design cost-aware architectures and clearly communicate cost trade-offs to engineering and business stakeholders.
• Proficiency in at least one programming language used in data platform work (Python, Java or Scala); SQL fluency is essential.
• Experience operating production data services — observability, alerting, incident response and post-incident review
• Excellent written and verbal communication and the ability to present to both technical and nontechnical stakeholders.
• Able to work independently, self-organise, scope work and adapt to changing requirements in a fast-paced environment
• Будет плюсом: Hands-on experience with AWS and its data-adjacent services (e.g. MSK, EKS, RDS, S3, DMS, KMS, CloudWatch, Secrets Manager); Production experience with Apache Kafka and Apache Flink, including stateful processing, exactly once patterns, and schema design; Experience implementing change data capture against relational sources and integrating with streaming platforms; Deep expertise in Snowflake, including Snowpark, data sharing, virtual warehouse sizing, and governance features (masking policies, row-level security, object tagging); Familiarity with AWS resource tagging strategies, cost allocation tags, and FinOps tooling; Understanding of Model Context Protocol (MCP) and how it enables AI agents to interact with data platform services to automate workflows and accelerate platform operations; Experience with data catalogue or metadata management tooling (e.g. Alation or equivalent)

• Competitive salary structure including company bonus scheme
• Flexible and hybrid working
• Remote working option - work from anywhere for up to 4 weeks per year
• 10 days of Company paid sick leave annually
• 21 days of paid vacation within the first year of employment, increasing to 25 days after one year
• 3 paid volunteering days per year & Workplace Giving Program
• Comprehensive medical insurance with coverage for your healthcare needs
• Pension fund
• Employee referral bonuses for referring top talent to the company
• Ongoing personal development & learning opportunities
• Periodic recognition and reward programs for outstanding performance and achievements
• Frequent events and celebrations
• Genuinely collaborative and friendly culture
• Employee Assistance Program & Wellbeing Initiatives
• Convenient and cozy office located near the Limassol Municipal Garden