Data Engineers design, build, and maintain the architecture that enables organisations to store, process, and access data at scale. This includes data pipelines, data warehouses, data lakes, and real-time streaming systems.

With more companies striving to harness the value of their data, demand for skilled Data Engineers is booming. It’s a fast-growing field with high potential for career development and innovation.

• Data Engineer
• Big Data Engineer
• Data Developer
• BI (Business Intelligence) Engineer
• BI Developer
• Business Intelligence Developer
• Business Intelligence Engineer
• Big Data Developer
• Hadoop Developer
• Data Factory Developer
• Hadoop Engineer
• Data Availability Engineer
• Data Science Engineer
• Big Data Software Engineer
• Platform Engineer
• Data Warehouse Engineer (DWH Engineer)
• DWH Programmer
• DWH Developer
• Datawarehouse Developer
• Datawarehouse Engineer
• SQL Server Engineer
• Data Infrastructure Engineer
• Data Infrastructure Programmer
• Data Infrastructure Developer
• Data Analytics Engineer
• Big Data Architect
• Hadoop Architect
• Hadoop Specialist
• Big Data Specialist
• Big Data Lead
• Head of Big Data

• Junior Data Engineer
• Data Engineer
• Senior Data Engineer
• Lead Data Engineer
• Head of Data Engineering
• Data Architect

We’ve outlined the latest salary benchmarks for Data Engineering roles in the guides below:

Data, Insight and Analytics Salary Guide

Data, Insight and Analytics Day Rate Guide

Data, Insight and Analytics Within Data Engineering Development Salary Guide

Data, Insight and Analytics Within Data Science Salary Guide

Core technical skills: SQL | ETL/ELT Development | Data Warehousing (Snowflake, Redshift, BigQuery) | Data Lake Technologies (AWS S3, Azure Data Lake) | Cloud Platforms (AWS, Azure, Google Cloud) | Programming (Python, Java) | Big Data Technologies (Apache Spark, Kafka, Hive, Airflow, dbt) | Streaming Data Processing (Kafka Streams, Apache Flink) | Workflow Orchestration (Apache Airflow, Luigi, Prefect) | Containerization & Orchestration (Docker, Kubernetes) | Infrastructure as Code (Terraform, CloudFormation) | API Development & Integration (RESTful APIs, GraphQL) | Monitoring & Logging (Prometheus, Grafana, ELK Stack) | Security & Compliance (encryption, access control, GDPR, HIPAA) | Performance Tuning & Optimization | Testing & Validation | Version Control & CI/CD (Git, Terraform, Docker)

Soft skills: Problem-solving & Critical Thinking | Collaboration & Cross-team Communication | Attention to Detail | Communication | Project Management & Agile Methodologies | Continuous Learning & Adaptability

Most Data Engineers hold a BSc, MSc, or PhD in a related discipline such as mathematics, physics, statistics, computer science, software engineering, artificial intelligence, or engineering.
While academic background is important, hands-on experience with large-scale datasets, data engineering tools, and cloud platforms (e.g. AWS, Azure, GCP) is often just as critical. Many employers value a strong portfolio of practical projects, contributions to open-source tools, or demonstrable knowledge of industry-standard platforms.

Salary: £28k – £38k
What They Do:
Assists in building and maintaining data pipelines, cleaning and transforming raw data, and supporting analytics teams with reliable datasets.

Skills Needed:

• Basic SQL and Python skills
• Understanding of ETL processes
• Familiarity with cloud data platforms (AWS, GCP, Azure)
• Knowledge of databases (relational and NoSQL)
• Strong problem-solving and debugging abilities

Salary: £38k – £50k
What They Do:
Designs, develops, and manages scalable data pipelines and systems that deliver clean, reliable data for business intelligence and analytics.

Skills Needed:

• Proficiency in SQL, Python, or Scala
• ETL tools and data integration (dbt, Airflow, Talend)
• Data modelling and warehousing
• Cloud platform experience (Snowflake, Redshift, BigQuery)
• Data quality and governance awareness

Salary: £50k – £70k
What They Do:
Leads complex data pipeline projects, improves performance and reliability of data systems, and mentors junior engineers.

Skills Needed:

• Advanced data architecture and pipeline design
• Real-time data streaming (Kafka, Spark Streaming)
• Automation and orchestration (Airflow, Luigi)
• Optimisation of large-scale data processing
• Strong collaboration with data scientists and analysts

Salary: £70k – £90k
What They Do:
Manages data engineering teams, sets best practices, and ensures enterprise-wide data platforms are scalable, secure, and high-performing.

Skills Needed:

• Leadership and team management
• Data platform strategy and roadmap
• Vendor and technology evaluation
• Data governance and compliance expertise
• Budgeting and resource allocation

Salary: £90k – £120k
What They Do:
Defines the organisation’s data engineering strategy, builds high-performing teams, and aligns data infrastructure with business needs.

Skills Needed:

• Department-level leadership and strategic planning
• Scaling data engineering capabilities
• Strong commercial awareness and vendor management
• Driving enterprise data strategy
• C-suite stakeholder engagement

Salary: £120k – £150k+
What They Do:
Owns the company’s data engineering and infrastructure vision, enabling enterprise-wide analytics, AI, and digital transformation.

Skills Needed:

• Executive-level leadership and data strategy
• Building global data engineering teams
• Expertise in compliance, governance, and security
• Investment planning for data technologies
• Driving innovation through data platforms