Data Engineer

Xcede

Greater London

Hybrid

GBP 55,000 - 75,000

Full time

14 days+

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Benefits offered by this job

Hybrid and flexible working

Professional development opportunities

Modern tech stack

Job summary

A fast-growing entertainment company is seeking a Senior Recruitment Consultant for Data & Analytics Engineering. You will build scalable data pipelines, work with modern tools like Apache Kafka, and contribute to data-driven decisions. This position allows for hybrid and flexible working, with opportunities to grow into senior roles. Ideal candidates have 2–3 years in data engineering and strong SQL skills.

Qualifications

2–3 years of experience in data engineering or a similar role.
Strong SQL skills and proficiency in at least one programming language (ideally Python).
Understanding of data warehousing concepts and ETL/ELT patterns.
Experience with version control (Git), testing, and code review practices.
Familiarity with cloud-based data environments (AWS, GCP or Azure).
Exposure to Airflow, dbt, Snowflake and streaming tools like Kafka.

Responsibilities

Build and maintain reliable, scalable data pipelines.
Develop and support real-time data workflows using Apache Kafka.
Monitor and ensure data quality, reliability, and security.
Monitor and ensure data quality, reliability, and security across the stack
Contribute to the evolution of data engineering practices, tooling, and automation
Collaborate with analytics, product, and data science teams to make data accessible and trustworthy

Skills

Data engineering

SQL

Python

Cloud technologies

Familiarity with cloud data environments (AWS, GCP, Azure)

Interest in streaming technologies (Apache Kafka)

Kafka

MLOps

Tools

Apache Kafka

AWS

Airflow

Snowflake

Job description

Senior Recruitment Consultant - Data & Analytics Engineering

A fast-growing entertainment company is expanding its data engineering team to build a modern, scalable data foundation that powers analytics, experimentation, and machine learning across the business.

Data plays a key role in how the company grows, innovates, and delivers great experiences for its users. You’ll work alongside experienced engineers and data scientists to shape and evolve the platform that underpins all data-driven decisions — including the development of real-time streaming capabilities using tools like Kafka.

This is a great opportunity for someone with early career experience in data engineering who’s ready to deepen their technical expertise and make a tangible impact in a creative, fast-paced environment.

Key Responsibilities:

Build and maintain reliable, scalable data pipelines for structured, semi-structured, and streaming data
Design and improve data models to support analytics and machine learning use cases
Develop and support real-time data workflows using technologies such as Apache Kafka
Monitor and ensure data quality, reliability, and security across the stack
Contribute to the evolution of data engineering practices, tooling, and automation
Collaborate with analytics, product, and data science teams to make data accessible and trustworthy

You will have:

2–3 years of experience in data engineering or a similar role
Strong SQL skills and proficiency in at least one programming language (ideally Python)
Understanding of data warehousing concepts and ETL/ELT patterns
Experience with version control (Git), testing, and code review practices
Familiarity with cloud-based data environments (e.g. AWS, GCP, or Azure)
Exposure to modern data tools such as Airflow, dbt, or Snowflake
Experience or strong interest in streaming technologies like Apache Kafka
Interest in MLOps and modern data engineering best practices

You’ll be part of a company with a clear mission and strong data culture, joining a team that values learning, collaboration, and creativity. The role offers real opportunities to grow towards senior and platform-focused positions, working with a modern tech stack and talented peers.

Package & Setup: