Data Engineer

About Insurance Insider

Insurance Insider is the leading source of actionable intelligence for the global insurance, reinsurance and
ILS markets. Our deeply sourced reporting and exclusive data tools give senior leaders the clarity they need
to anticipate shifts and make confident decisions. As we scale our subscription and intelligence products,
we’re building a commercial engine that matches the pace and ambition of our journalism. Joining the team
means working inside a business that moves markets, where sharp insight, experimentation and commercial
impact drive how we build, market and grow our platform.

About the Role
We are looking for a mid-level Data Engineer who writes real code, builds robust pipelines, and takes
ownership of data infrastructure from end to end. You will be comfortable across Python, TypeScript, and
Node.js, and will use AI tools to work efficiently and ship high-quality solutions. This role spans data
engineering, analytics configuration, and content integration — giving you broad exposure across the stack
without losing depth in the engineering fundamentals. You bring a few years of solid experience, have strong
opinions about good pipeline design, and can operate independently while collaborating closely with
product, editorial, and commercial teams.

Key Responsibilities:
• Data Engineering & Pipeline Development
o Design, build, and maintain data pipelines and orchestration workflows using Databricks,
Python, and TypeScript/Node.js — covering ingestion, transformation, scheduling, and
monitoring.
o Write clean, well-structured scripts and services to ingest, process, and transform data
from APIs, databases, and third-party sources — using Python for data work and
Node.js/TypeScript where appropriate for integrations or lightweight services.

• Analytics & Insights Configuration
o Configure and maintain dashboards, reports, and analytics tools to surface insights from
content and data — connecting pipeline outputs to BI tools and keeping metrics accurate
and up to date.
o Work closely with editorial, product, and commercial teams to understand their data needs
and translate them into practical metrics and visualisations.

• Content & Data Integration
o Connect content assets with structured data using scripted pipelines — enabling smarter
search, tagging, categorisation, and intelligence features across our platform.
o Identify new data sources and APIs, scope their integration, and build the connectors
needed to operationalise them — fast.

• AI-Assisted Development
o Leverage AI coding tools (e.g. GitHub Copilot, Claude, Cursor) to write, debug, and iterate on
data scripts, pipelines, and orchestration logic quickly and independently.
o Stay curious and self-directed — experiment with new tools and approaches, and bring
practical solutions to the team without waiting for perfect resources or large teams.
o Develop working prototypes for AI based products and/or AI internal tools

• Stakeholder Collaboration
o Work across teams — product, editorial, commercial, and leadership — to understand data
needs and surface the right insights at the right time.
o Communicate data findings clearly to non-technical audiences, making complex outputs
accessible and actionable.

• Operational Excellence
o Monitor data quality across pipelines and outputs, flagging issues proactively and
implementing fixes to maintain reliable, trustworthy data.
o Continuously improve data processes, tooling, and documentation so that the team’s data
assets are scalable, maintainable, and easy to build on.

Required Experience
• 3–5 years of hands-on software or data engineering experience, with strong proficiency in Python and
working knowledge of TypeScript or Node.js — comfortable writing production-quality code, not just
scripts.
• Proven experience designing and running data pipelines and orchestration workflows in production
— with solid understanding of scheduling, dependency management, retries, alerting, and data
quality patterns.
• Solid experience with Databricks, Spark, or a comparable cloud data platform; confident with SQL,
Delta tables, and both notebook-based and job-based pipeline architectures.
• Experience connecting data pipelines to analytics or BI tools (e.g. Power BI, Looker, Metabase) and
maintaining the data models that underpin them.
• A strong engineering foundation combined with a generalist mindset — able to move between data
engineering, analytics, integration work and prototype development and make sound technical
decisions independently.
Preferred Qualifications
• A degree in Computer Science, Engineering, or a related technical field — or demonstrably
equivalent experience. We care more about the quality of your engineering than where you studied.
• Experience with orchestration tools such as Airflow, Dagster or Databricks Workflows; confident
building REST API integrations, webhook consumers, or event-driven data patterns in Node.js or
Python.
• Demonstrated use of AI coding assistants (e.g. Copilot, Claude, Cursor) as a genuine multiplier —
not a crutch. You write good code, use AI to go faster, and know the difference.

What We Offer:
• Competitive salary and benefits package.
• Opportunity to work in a fast-paced, supportive and innovative environment.
• Career growth and development opportunities.
• Flexible working hours.
• Great team and positive working environment

If you are passionate about development and data and are looking for a challenging role in a company
that values growth, collaboration, and innovation, we would love to hear from you!