Analytics Engineer
BoomingTransforming raw warehouse data into clean, documented datasets analysts can trust
Analytics Engineer Salary
United Kingdom
£50,000 – £85,000
United States
$95,000 – $150,000
Varies by location, sector, and experience. Last updated: 2025.
What Is an Analytics Engineer?
An Analytics Engineer sits between data engineering and data analysis. They take raw data that has been loaded into a data warehouse and transform it into clean, well-structured, documented datasets that analysts and business users can trust and query confidently. The role emerged from the modern data stack — particularly the adoption of dbt — and has grown rapidly as organisations invest in making their data reliably usable at scale. It is most common in technology companies, scale-ups, and data-mature organisations across financial services, retail, and media.
Unlike a Data Engineer who builds ingestion pipelines, or a Data Analyst who produces reports, an Analytics Engineer focuses on the transformation layer — writing modular SQL models in dbt, defining metrics consistently across the business, testing data quality, and maintaining documentation so that the logic behind every dataset is auditable. The work is highly collaborative, sitting at the intersection of the data team and the business functions that depend on accurate data, and requires both technical rigour and enough domain understanding to model data in ways that reflect how the business actually operates.
What Does a Analytics Engineer Do?
- Build and maintain data transformation models using dbt and SQL to produce reliable, analytics-ready data assets
- Design and implement a layered data modelling architecture across staging, intermediate, and mart layers for consistent consumption
- Define and standardise business metrics in the semantic layer to ensure consistent calculation and reporting across teams
- Write and maintain dbt data quality tests to catch upstream data issues before they reach analysts and dashboards
- Monitor data pipeline health and investigate data quality incidents, identifying root causes and coordinating fixes with upstream teams
- Collaborate with data engineers on ingestion requirements and with analysts on mart design and reporting needs
Analytics Engineer Skills
Hard Skills
- SQL
- Data Modelling
- ETL Pipeline Design
- Data Quality Management
- Data Pipeline Orchestration
- Data Governance
- Version Control
- Statistical Modelling
- Dashboard Design
- Requirements Gathering
Soft Skills
- Analytical ThinkingDesigning transformation logic for reliable data models
- Attention to DetailData quality testing and metric consistency
- CollaborationBridging data engineering and business analyst teams
- CommunicationAligning on metric definitions across the organisation
- Documentation DisciplineMaintaining dbt model documentation and lineage
- OwnershipAccountable for transformation layer reliability and trust
Analytics Engineer Tools & Software
How to Become a Analytics Engineer
Typical Route
Most Analytics Engineers hold a bachelor's degree in Computer Science, Statistics, Mathematics, or Economics. The role draws heavily from both software engineering and quantitative analysis, and programs at the University of Washington, Georgia Tech, and the University of Texas at Austin provide relevant foundations across both tracks. Many practitioners move into analytics engineering from data analyst or SQL-heavy business intelligence roles rather than entering directly after graduation. A master's degree in Data Science or Computer Science supports progression into senior positions.
Alternative Route
The dbt Certified Developer credential is the most directly relevant qualification and is increasingly recognised by US employers. Snowflake and Google Cloud certifications support platform-specific progression. Coursera and DataCamp offer structured dbt, SQL, and data modelling courses accessible to US learners. A strong GitHub portfolio demonstrating dbt projects, clean SQL modelling, and documented data transformation work is widely cited by hiring managers as the most compelling evidence of readiness — more so than certifications alone for this role.
A Day in the Life of an Analytics Engineer
Morning
Afternoon
Analytics Engineer Career Path
Data / Business Analyst
0–3 yrs
Analytics Engineer
3–5 yrs
Senior Analytics Engineer
5–7 yrs
Staff Analytics Engineer
7–9 yrs
Data Platform Lead / Head of Data
9+ yrs
Analytics Engineer Job Outlook
Analytics Engineering is one of the fastest-growing roles in the data space, driven by investment in modern data stacks across financial services, technology, and e-commerce. As organisations shift toward self-service analytics, the need for engineers who can build reliable transformation layers is accelerating. dbt adoption has created a distinct and well-compensated specialism that did not exist at scale five years ago. The talent pool remains small relative to demand, sustaining a consistent shortage at mid-to-senior levels.