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About the Company

We focus on delivering exceptional returns through practical execution of tailored solutions, integrating strategy, product, design, engineering, and data to solve complex financial technology challenges. Collaborating as a unified, accountable team, we own outcomes rather than simply producing outputs. Currently, we are steering transformation efforts within one of the UK’s leading financial institutions—a global trading platform aiming to surpass its present capabilities. Our initiative reshapes product development, value creation, technology implementation, and data-driven decision-making. You will be the second data professional appointed to support this transformation.

Role Overview

This position is not centered on routine reporting or support tasks. Instead, it demands strong technical expertise and accountability. You will join the foundational team responsible for establishing the core data infrastructure upon which all other systems will rely. Your scope includes handling authentication, onboarding, and account-related systems—crucial touchpoints that every user interacts with.

Serving as the primary analytical collaborator to engineering teams working on these pivotal services, your mission is to integrate deeply into the Software Development Lifecycle, ensuring that every microservice, API, and frontend element is robustly instrumented, monitored, and analyzed.

Why This Role Is Unique

Engineering teams progress rapidly but often lack native event-tracking and experimentation disciplines. Your role is proactive and influential: rather than creating dashboards on demand, you will actively participate in development ceremonies, collaborate closely with backend engineers, scrutinize release features, uphold quality monitoring standards, lead experimentation governance, and enforce telemetry compliance, paving the way for future best practices.

Current Environment

You will join a high-speed squad alongside backend leaders focused on critical transitions such as merging legacy users via Auth0. Your role bridges backend system performance with user behavior analytics, converting raw event stream data into actionable insights.

Key Responsibilities

Ownership of identity and session stitching logic, tracking user behavior seamlessly across microservices, APIs, and external tools—from anonymous usage through authenticated accounts.
Managing observability and user experience monitoring intersections, utilizing tools like AWS RUM, Datadog, New Relic, and Amplitude to pinpoint client-side errors, crashes, and latency issues impacting users.
Monitoring the authentication and onboarding funnel closely to identify configuration failures and tracking integration issues, particularly related to the Auth0 migration.
Partnering with developers to audit sprint tickets, verifying that behavioral telemetry and event tagging are part of completion criteria before any code release.
Collaborating with infrastructure teams to manage ingestion and streaming of high-volume event data (using AWS Kinesis, Kafka), ensuring analytics pipelines scale with backend service traffic.
Defining success metrics for new features or data views, establishing A/B testing frameworks to measure real-world impact.

Working Approach

You will be an outspoken contributor in engineering rituals, advocating a culture of A/B testing and telemetry where previously absent. Leveraging AI and modern data workflows, you will automate anomaly detection and QA processes, enabling a concentration on architectural and strategic initiatives.

Success Metrics

Every feature released includes validated event tracking and performance monitoring integrated into its development ticket.
User identity resolution is consistent end-to-end, maintaining session continuity from initial app download through full account authentication.
Engineering leadership depends on your observability tools to detect callback errors and application crashes proactively, preventing negative impact on executive-level metrics.
Experimentation, A/B testing, and enhanced data outputs are embedded as standard engineering practices rather than afterthoughts.

Candidate Requirements

At least 5 years of experience in analytics engineering, DevOps, or data engineering roles closely collaborating with software development teams.
In-depth knowledge of identity stitching and session management, especially within complex Auth0 and migration contexts.
Proficiency with observability and Application Performance Management platforms such as Datadog and New Relic alongside behavioral analytics tools like Amplitude or Mixpanel.
Experience working with event streaming pipelines including AWS Kinesis or Kafka, and translating backend event data into actionable product metrics.
Proven track record integrating quality assurance and data standards within agile/SDLC environments using tools such as Jira, Trello, or Linear.
Advanced skills in SQL and Python for data transformation and process automation.
Preferred: experience with multiproduct fintech or trading platforms undergoing legacy technology migrations.
Familiar with modern deployment methodologies and instrumentation of backend microservices or monolithic systems.
Comfortable challenging senior engineers to enforce stringent data quality standards before product release.

Benefits

Competitive compensation aligned with experience.
End-of-service benefits and performance bonuses on par with market standards.
Comprehensive health insurance coverage.
Budgets allocated for professional growth and attending industry conferences.
Opportunities for team-building, mentorship, and engaging company culture.
Flexible remote work arrangements.

Data Lead