Data Engineer

Inforcer; Greater London; On-site; GBP 75,000 - 110,000; Full time

Job summary

Inforcer in London is seeking a Data Engineer to design, build and maintain the infrastructure powering our automation and AI platforms. You will develop scalable data pipelines, integrate data from multiple systems and lay the foundations of a modern data lake architecture.

Work with stakeholders to ensure data is accessible, reliable and ready for analytics, reporting, automation, and AI initiatives. You will tackle complex data challenges and implement robust integrations to support rapid

Qualifications

• Proven experience as a Data Engineer or in a similar role.
• Strong SQL skills and experience with large datasets.
• Commercial experience building ETL/ELT pipelines.
• Experience developing data integrations and ingestion frameworks.
• Strong Python development skills.
• Experience working within cloud-based data environments.
• Knowledge of data modelling and database design principles.
• Experience with Microsoft Azure and Azure Data Lake Storage (ADLS).
• Experience with data engineering tools such as Azure Data Factory, Databricks, Apache Spark, dbt or Airflow.
• Experience with cloud data platforms such as Azure Synapse Analytics or Snowflake.
• Experience using Git for version control.
• Experience integrating REST APIs and working with event-driven architectures.
• Knowledge of Kafka or other streaming technologies.
• Understanding of change data capture (CDC) patterns.
• Knowledge of data governance and master data management practices.

Responsibilities

• Design and maintain a scalable data lake and modern data platform architecture.
• Develop efficient data storage solutions for structured and unstructured datasets.
• Support data governance, security and compliance requirements.
• Optimise data models and storage performance.
• Develop and maintain data ingestion frameworks for internal and external systems.
• Build integrations across SaaS platforms, databases, APIs and third-party applications.
• Implement batch and real-time data ingestion patterns.
• Manage data synchronisation and change data capture (CDC) processes.
• Design, develop and maintain ETL/ELT pipelines.
• Transform raw data into trusted, business-ready datasets.
• Monitor pipeline performance and proactively resolve issues.
• Improve reliability, scalability and automation across the data estate.
• Implement data validation and quality controls.
• Create monitoring and alerting mechanisms for critical pipelines.
• Troubleshoot data issues and conduct root cause analysis.
• Ensure high levels of availability and integrity across the platform.
• Work closely with business stakeholders, analysts, engineers and leadership teams.
• Support reporting, analytics and AI initiatives through reliable data delivery.
• Contribute to data architecture decisions and platform roadmaps.
• Document solutions and promote engineering best practices.

Skills

Data Engineering

SQL

ETL/ELT

Data Integrations

Python

Cloud Data

Data Modelling

Azure

Azure Data Factory

Databricks

Apache Spark

dbt

Airflow

Git

REST APIs

Kafka

CDC

Data Governance

Tools

Azure Data Factory

Databricks

Apache Spark

dbt

Airflow

Snowflake

Azure Synapse Analytics

Job description

About Us

inforcer is one of the fastest growing technology organisations in the world and a leading provider of cutting-edge cybersecurity and AI solutions to support to the SMB market. We provide MSPs (Managed Service Providers) with the fundamental technology they need to manage and secure Microsoft 365 at scale and deliver AI services. Our mission is to beinforcedin every MSP!

About the Role

We're looking for a Data Engineer to design, build and maintain the infrastructure that powers our internal automation and AI platforms.

You'll develop scalable data pipelines, integrate data from multiple business systems and build the foundations of a modern data lake architecture. Working closely with internal stakeholders, you'll ensure data is accessible, reliable and ready to support analytics, reporting, automation and AI-native initiatives.

This role is ideal for someone who enjoys solving complex data challenges, building robust integrations and creating scalable solutions that support rapid business growth. If this sounds like you, we'd love to hear from you.

What you'll be doing

• Design and maintain a scalable data lake and modern data platform architecture
• Develop efficient data storage solutions for structured and unstructured datasets
• Support data governance, security and compliance requirements
• Optimise data models and storage performance
• Develop and maintain data ingestion frameworks for internal and external systems
• Build integrations across SaaS platforms, databases, APIs and third-party applications
• Implement batch and real-time data ingestion patterns
• Manage data synchronisation and change data capture (CDC) processes
• Design, develop and maintain ETL/ELT pipelines
• Transform raw data into trusted, business-ready datasets
• Monitor pipeline performance and proactively resolve issues
• Improve reliability, scalability and automation across the data estate
• Implement data validation and quality controls
• Create monitoring and alerting mechanisms for critical pipelines
• Troubleshoot data issues and conduct root cause analysis
• Ensure high levels of availability and integrity across the platform
• Work closely with business stakeholders, analysts, engineers and leadership teams
• Support reporting, analytics and AI initiatives through reliable data delivery
• Contribute to data architecture decisions and platform roadmaps
• Document solutions and promote engineering best practices

What We Can Offer You

Steep Learning curve: We believe people leave organisations when learning stops. We promise a steep and continuous learning curve to both challenge and develop our people. You are responsible for your own learning, but you'll be surrounded by exceptional people and strong enablement, if you choose to lean into it, in an environment where it's safe to make mistakes, try new things, and improve.

Real impact:We operate in a high-trust and autonomous environment where you can make a real impact and difference in your role and across the company.

Transparency and Honesty:We believe honest and clear communication creates a highly collaborative culture. It gives you the “why” we make decisions and allows you to effectively make your own. We won't pull the wool over your eyes, we are a fast-growing start-up that comes with its own unique challenges, but we all work hard to solve them, together, as a team.

A+ Global Team: Our people power every part of our business, and we look for individuals who bring genuine passion to their role and operate at their very best. A-players thrive when surrounded by other A-players. Our level of growth and rate of change can be hard work and challenging, but you'll be surrounded with exceptional people that are always happy to help.

Regular Team Socials:We celebrate our team, our milestones, promotions and achievements with social events every month.

Employee Recognition:Programs to recognise and reward our top contributors for their achievementsand efforts. We live our company values every day and reward those people who embody them.

Skills We Need for This Role

• Proven experience as a Data Engineer or in a similar role
• Strong SQL skills and experience working with large datasets
• Commercial experience building ETL/ELT pipelines
• Experience developing data integrations and ingestion frameworks
• Strong Python development skills
• Experience working within cloud-based data environments
• Knowledge of data modelling and database design principles
• Experience with Microsoft Azure and Azure Data Lake Storage (ADLS)
• Experience with data engineering tools such as Azure Data Factory, Databricks, Apache Spark, dbt or Airflow
• Experience with cloud data platforms such as Azure Synapse Analytics or Snowflake
• Experience using Git for version control
• Experience integrating REST APIs and working with event-driven architectures
• Knowledge of Kafka or other streaming technologies
• Understanding of change data capture (CDC) patterns
• Knowledge of data governance and master data management practices
• A collaborative approach with the ability to communicate clearly with technical and non-technical stakeholders

Inforcer is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.