Principal Recruiter
Data, Insight & Analytics
View profileAnalytics engineering bridges the gap between data engineering and data analysis. By transforming raw data into clean, reliable, well-documented datasets, analytics engineers make data more accessible and usable for business intelligence, reporting, and decision-making. It ensures that stakeholders (technical or otherwise) can trust and act upon high-quality, well-structured data.
For more about Analytics Engineering, please review our blogs on this topic:
Part one: Analytics Engineering: Modern Data Teams
Part two: The Rise of Analytics Engineers: The Modern Data Stack
Part three: Key Skills and Tools for Analytics Engineers: Building the Future of Data
Part four: The Power Trio: DBT, Looker, and Snowflake in Analytics Engineering
Part five: Here’s Why Companies Should Hire Analytics Engineers
Why consider a career in Analytics engineering ?
With the increasing demand for data-driven decision-making, analytics engineering has emerged as a crucial role within modern data teams – they’re becoming more and more popular, with many companies adopting new AE teams or individuals.
It offers exciting opportunities to work across both technical and strategic areas, combining engineering practices with analytical insight. For those passionate about data quality, modelling, and enabling data use at scale, it’s a rewarding and fast-evolving career path.
What are typical Analytics engineering job titles?
- • Analytics Engineer
• Data Analytics Engineer
• BI Engineer (Business Intelligence Engineer)
• Data Engineer, Analytics
• Analytics Data Engineer
• Data Platform Engineer (Analytics-focused)
• Reporting Engineer
• Data Insights Engineer
• Data Modeling Engineer
• ETL Engineer (if heavily focused on pipelines for analytics)
• Senior Analytics Engineer
• Lead Analytics Engineer
• Principal Analytics Engineer
• Staff Analytics Engineer
• Head of Analytics Engineering
• Analytics Engineering Manager
• Director of Analytics Engineering
• Analytics Infrastructure Engineer
• Data Platform Engineer (Analytics-focused)
• Analytics Pipeline Engineer
Analytics Engineering: Career Progression Example
- Analytics Engineer
- Senior Analytics Engineer
- Lead Analytics Engineer
- Head of Analytics Engineering
- Data Architect / Analytics Engineering Manager
Analytics Engineering Salary Benchmarks
View our Data, Insight and Analytics within Engineering and Development Salary Guide
Analytics Engineering: Is It Right for Me? The Skills It Takes…
Analytics engineers require a blend of engineering acumen, data modelling capability, and strong communication skills. Key skill areas include:
Engineering & Technical Skills: Data Modelling (Star and Snowflake Schemas) | Snowflake | Looker | dbt | Airflow | ELT Pipelines | Fivetran | Advanced SQL | Cloud Data Warehouses including BigQuery, Snowflake, and Redshift | Git and Version Control | CI/CD for Data Workflows | Testing and Documentation of Data Pipelines | Data Lineage and Metadata Management
Analytical & Communication Skills: Translating Business Logic into Data Models | Collaboration with Analysts and Stakeholders | Clear and Concise Documentation, including Data Dictionaries | Strong Data Literacy and Identification of Data Quality Issues | Communicating Insights and Trade-offs to Non-Technical Audiences
Tooling & Platform Knowledge: dbt (Data Build Tool) | Looker, Tableau, and Power BI (for validation and collaboration) | SQL-based Transformation Tools | GitHub and GitLab for Workflow and Collaboration | Cloud Platforms including GCP, AWS, and Azure
What qualifications do you need for a career in Analytics engineering?
Most employers look for a Bachelor’s degree (or equivalent) in a technical or analytical subject such as Computer Science, Data Science, Mathematics, or Statistics. However, due to the emerging nature of the role, individuals with relevant experience in data analysis, data warehousing, or data engineering – especially those who’ve gained hands-on experience with the modern data stack (dbt, Looker, Snowflake) – are also well-placed to move into analytics engineering roles.
CAREER PATH
This guide maps out the progression of roles in Analytics Engineering, from entry-level positions through to senior leadership, including job descriptions, salary bands, and key skills for the UK market.
Junior Analytics Engineer / Data Engineer (Entry-Level)
Salary: £28k – £38k
What They Do:
Supports the design and maintenance of data pipelines and analytics infrastructure, transforming raw data into usable datasets for analysts and data scientists.
Skills Needed:
- Basic SQL and database knowledge
- Understanding of ETL processes
- Exposure to cloud platforms (AWS, GCP, Azure)
- Python or R for data manipulation
- Strong problem-solving and data wrangling skills
Analytics Engineer
Salary: £38k – £50k
What They Do:
Builds robust data models, ensures data quality, and collaborates with analysts and engineers to improve reporting and analytics capabilities.
Skills Needed:
- Proficient in SQL and data modeling
- Experience with BI tools (Looker, Tableau, Power BI)
- Automation of ETL pipelines (Airflow, dbt, Stitch)
- Data warehousing solutions (Snowflake, BigQuery, Redshift)
- Knowledge of version control (Git)
Senior Analytics Engineer
Salary: £50k – £65k
What They Do:
Designs and scales data infrastructure, implements advanced analytics solutions, and mentors junior engineers.
Skills Needed:
- Advanced data modeling and transformation
- Optimising data pipelines for performance
- Expertise in cloud data platforms
- Governance and data quality frameworks
- Stakeholder management and project delivery
Analytics Engineering Lead / Data Engineering Lead
Salary: £65k – £80k
What They Do:
Manages analytics engineering teams, sets best practices, and ensures data systems support business decision-making.
Skills Needed:
- Leadership and team management
- Enterprise-level data architecture
- Budget and resource planning
- Knowledge of security, compliance, and data privacy
- Strong cross-functional collaboration
- Basic understanding of PR tools (e.g. Gorkana, Cision)
Head of Analytics Engineering / Director of Data Engineering
Salary: £80k – £110k
What They Do:
Leads the organisation’s analytics engineering strategy, ensuring scalable, reliable, and secure data systems.
Skills Needed:
- Department-level leadership and vision
- Enterprise data strategy and roadmap
- Building and scaling data engineering teams
- Vendor and technology partner management
- KPI definition and alignment with business objectives
Chief Data Officer / VP of Data & Analytics
Salary: £120k – £150k+
What They Do:
Defines the data and analytics vision at the board level, drives digital transformation through data, and ensures analytics are embedded in business operations.
Skills Needed:
- Executive-level leadership and strategic vision
- Expertise in data governance and compliance
- Driving enterprise-wide data culture and literacy
- Strong communication with C-suite and stakeholders
- Investment planning for data and analytics initiatives
Our Data, Insight & Analytics recruitment team
-
Tegan Fenn
JOB
SEARCH
Our latest Data, Insight & Analytics jobs
We connect ambitious organisations with their greatest assets, equally ambitious talent.
Product Data Analyst (12 Month FTC)
Purpose Driven
Help shape data products that drive better decisions across a complex, fast-moving business.
Join a collaborative product team working at the heart of data and analytics.
Work with Snowflake, SQL and BI tools.
Full details
07th Jul
AI Solutions Engineer
Build AI agents, intelligent applications and enterprise solutions used across an entire organisation.
Help shape a brand-new AI capability with genuine freedom to influence its direction.
Build enterprise-scale AI products, agents and LLM-powered applications used across the business.
Full details
07th Jul
Data Science Lead (12 Month FTC)
Purpose Driven
Lead a high visibility data science function and shape business decisions at the highest level.
Lead a small but impactful data science team and influence senior stakeholders across the business.
Work on forecasting, machine learning and AI initiatives using Databricks, Python and modern analytics tools.
Full details
03rd Jul
Data, Insight & Analytics case study
-
We provided salary bandings plus information about motivations for moving and skills that are in demand, leading to the placement of 3 Cloud Data Engineers including a lead after approving salaries and agency budget.
-
Client Testimonial by Lulu Crosthwaite-Eyre, Managing Director of Cygnus Instruments: “ADLIB took the time to understand our unusually ‘human’ company culture, as well as the skills, experience and location requirements of the roles. We worked with 2 recruiters, from different teams within ADLIB, and care was taken to find an extremely good fit in each case. Both new starters settled in seamlessly and very quickly became valued members in their respective teams. I’m genuinely looking forward to working with ADLIB again.”
-
Client Testimonial by Michelle Stark, CMO of World Host Group: Working with a recruitment partner like ADLIB means you’re working with a group of people who get to understand you and match candidates up with your culture and goals. ADLIB worked at a breakneck speed to introduce us to the marketing experts we needed to build our team in a matter of months. With their help we recruited and onboarded a new team much faster than planned and ended up spoilt for choice because of the way they work and market insights.
-
Client Testimonial by Joss Ford, Founder of Enviral: "ADLIB have really gotten to know us over the years, truly understanding our business, mission and values. They’re our trusted partner and go to for hiring insight. Not only are they perfectly aligned with our B Corp values and understand how to run an inclusive process, but their track record is second to none. We knew we could trust them to find the very best candidates and to ensure the candidates in process had an excellent experience. It was especially helpful to receive their guidance when shaping the job description and title for the role. Forget using Exec Search firms, ADLIB is the one!"
-
Following significant Series A funding, LabGenius needed an expert Bioscience and Biotechnology recruitment partner to provide a scalable model for growing their Science and Technology teams.
-
Client Testimonial by Stephanie Fisher, CEO at Hello Earth: "It’s been like night and day working with ADLIB. Really impressed with how great the candidates have been, and how the team have been so responsive and totally on the ball. What a bunch of great people!"
-
FOLIUM Science needed an expert niche science recruitment partner with specific expertise in microbiome and genome engineering to help them secure highly skilled scientific talent efficiently.
-
Client Testimonial by Jake Smith, Operations Director at Space 48: "Space 48 has ambitious growth targets and recognises the importance of working with a recruitment partner that understands the business' vision and culture. The team at ADLIB has worked with us over the last 2+ years and has been instrumental in helping us to grow across several key disciplines. ADLIB spent the time to get to know Space 48 which meant they only introduce us to people who have the talent, attitude, and passion to be part of our great team. To Space 48, a recruitment partner is a long-term investment, and ADLIB continues to demonstrate its sector expertise and talent for finding the right people."
-
Client Testimonial by Tamara Miner, Director of Engineering at Climate Policy Radar: ADLIB collaborated closely with us, refining the process through an iterative approach, and helped us find six exceptional candidates for our growing tech team.
-
They needed to build the team. We worked with them to truly understand their style of working and management. This resulted in the team’s first 2 hires, followed by another 5 hires across data engineering and machine learning over an 18-month period.
Data, Insight & Analytics Salary guides:
- 0117 926 9530
- hello@adlib-recruitment.co.uk
- Company registered in England and Wales
- No: 5138584.
- Member of APSCo.