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
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Tegan Fenn
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MI Analyst (12 Month FTC)
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Data, Insight & Analytics case study
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ADLIB helped Malvern Panalytical locate top-tier candidates from graduate to senior level with skills in full-stack software development and quality assurance. The result is a dynamic and diverse Research and Development team that Malvern Panalytical are proud of.
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Zoe has been a fantastic recruitment partner for Colorifix over the past few years, successfully supporting us on a wide variety of mandates. She is quick to understand what is needed and consistently provides high quality candidates.
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Scala and Kafka were initial sticking points for the manager, so we pressed for suitable alternatives to increase the flexibility. They agreed to consider candidates with different streaming experience and programming backgrounds which opened a larger pool. We placed 3 highly technical hires.
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By choosing ADLIB as their Outsourced Recruitment Partner, TFSL ensured a timely and effective solution to their recruitment needs, securing a highly capable Marketing Manager in less than a month.
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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.
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“From finding me my current role to helping place two fantastic hires, ADLIB has been a pivotal role in the development of our team here at Bristol. The guys are easy to work with, friendly and most importantly inspire trust. I look forward to working with them in the future.”
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The Head of Data Engineering needed this team built fast, so we agreed to keep open lines of communication and for 24-hour CV turnaround and suggested streamlining the process as much as possible due to the nature of such a competitive talent market.
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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!
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GTSW is an incredible resource for expanding knowledge on the wider subject of sustainable technology. It’s helped to expand my network of environmentally focused tech folk. Enabling conversations, collaborations and new friendships. It’s a great community to be a part of.
Nick Lewis
Senior Sustainable Web Developer at Leap and creator of lowwwcarbon.com
Green Tech South West
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“ADLIB used their digital marketing expertise and network to source an amazing candidate quickly. This was such a smooth process down to ADLIB's knowledge and proactive nature.”
Data, Insight & Analytics Salary guides:
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