Salary for Mid-level / Intermediate Data Engineer in United Kingdom during 2022

Salary details

The average mid-level / intermediate Data Engineer salary lies between USD 73,880 and USD 92,350 in the United Kingdom. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Dec. 22, 2024

Salary trend

Top 20 Job Tags for Mid-level / Intermediate Data Engineer roles

The three most common job tag items assiciated with mid-level / intermediate Data Engineer job listings are Python, Engineering and SQL. Below you find a list of the 20 most occuring job tags in 2022 and the number of open jobs that where associated with them during that period:

Python | 513 jobs Engineering | 453 jobs SQL | 451 jobs Pipelines | 415 jobs AWS | 358 jobs Data pipelines | 299 jobs ETL | 287 jobs Spark | 241 jobs Computer Science | 224 jobs Azure | 223 jobs Machine Learning | 222 jobs Big Data | 196 jobs Agile | 196 jobs Architecture | 169 jobs APIs | 169 jobs GCP | 166 jobs Airflow | 165 jobs Scala | 149 jobs Redshift | 136 jobs NoSQL | 130 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Data Engineer roles

The three most common job benefits and perks assiciated with mid-level / intermediate Data Engineer job listings are Career development, Flex hours and Health care. Below you find a list of the 20 most occuring job perks or benefits in 2022 and the number of open jobs that where offering them during that period:

Career development | 434 jobs Flex hours | 230 jobs Health care | 229 jobs Startup environment | 182 jobs Team events | 161 jobs Competitive pay | 154 jobs Flex vacation | 120 jobs Equity / stock options | 105 jobs Parental leave | 93 jobs Salary bonus | 86 jobs Insurance | 69 jobs Medical leave | 61 jobs Gear | 44 jobs Unlimited paid time off | 43 jobs Wellness | 40 jobs Home office stipend | 40 jobs 401(k) matching | 37 jobs Conferences | 37 jobs Fitness / gym | 33 jobs Yoga | 28 jobs

Salary Composition for Mid-level Data Engineers in the UK

The salary for a mid-level data engineer in the UK typically comprises a fixed base salary, performance bonuses, and additional remuneration such as stock options or benefits. The base salary is the most significant component, often accounting for 70-85% of the total compensation package. Performance bonuses can vary widely, ranging from 5-20% of the base salary, depending on the company's performance and individual contributions. Additional remuneration might include stock options, especially in tech startups or larger tech firms, and benefits such as health insurance, pension contributions, and professional development allowances. The composition can vary significantly based on the region, with London-based roles often offering higher salaries due to the cost of living. Industry also plays a role; for instance, data engineers in finance or tech sectors might receive higher bonuses compared to those in public sector roles. Company size can influence stock options and benefits, with larger companies typically offering more comprehensive packages.

Steps to Increase Salary from a Mid-level Position

To increase your salary from a mid-level data engineer position, consider the following strategies:

• Skill Enhancement: Continuously update your technical skills, especially in emerging technologies like cloud computing, big data frameworks, and machine learning. Proficiency in tools like Apache Spark, Hadoop, and cloud platforms such as AWS, Azure, or Google Cloud can make you more valuable.

• Advanced Education: Pursuing a master's degree or specialized courses in data science or machine learning can open up higher-paying opportunities.

• Networking and Professional Visibility: Attend industry conferences, participate in webinars, and contribute to open-source projects. Building a strong professional network can lead to new job opportunities and salary negotiations.

• Certifications: Obtain relevant certifications that are recognized in the industry, which can validate your skills and potentially lead to salary increases.

• Leadership and Management Skills: Developing soft skills and taking on leadership roles within projects can position you for promotions to senior or managerial roles, which typically come with higher salaries.

Educational Requirements for Mid-level Data Engineers

Most mid-level data engineer positions require at least a bachelor's degree in computer science, information technology, engineering, or a related field. Some employers may prefer candidates with a master's degree, especially for roles that involve complex data architecture or machine learning components. A strong foundation in mathematics and statistics is also beneficial, as it underpins many data engineering tasks.

Helpful Certifications for Data Engineers

Several certifications can enhance your credentials as a data engineer:

• AWS Certified Data Analytics – Specialty: Validates expertise in using AWS data lakes and analytics services.
• Google Professional Data Engineer: Demonstrates proficiency in designing, building, and operationalizing data processing systems on Google Cloud.
• Microsoft Certified: Azure Data Engineer Associate: Focuses on implementing data solutions using Azure services.
• Cloudera Certified Professional (CCP) Data Engineer: Recognized for skills in data ingestion, transformation, and storage.

These certifications can help differentiate you in the job market and may lead to higher salary offers.

Experience Required for Mid-level Data Engineers

Typically, mid-level data engineer roles require 3-5 years of experience in data engineering or related fields. This experience should include hands-on work with data pipelines, ETL processes, and data warehousing solutions. Familiarity with programming languages such as Python, Java, or Scala, and experience with SQL and NoSQL databases are often expected. Experience with cloud platforms and big data technologies is increasingly important.

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