Analytics Engineer
SOC 15-1243.00 · ESCO 2511 · OSCA 223234
Role snapshot
Overview
An Analytics Engineer is a crucial link between raw data and actionable insights. They design, build, and maintain robust data pipelines and data models, transforming complex, disparate data sources into clean, reliable, and easily consumable datasets. This role involves writing efficient SQL queries, developing data transformation logic using tools like dbt, and ensuring data quality and governance within modern data warehouses to empower data analysts and business stakeholders.
Ensures data reliability and accessibility, enabling accurate reporting, advanced analytics, and data-driven decision-making across an organization.
On the job
- Design and implement scalable data models in data warehouses (e.g., Snowflake, BigQuery, Redshift)
- Develop, test, and maintain data transformation pipelines using SQL and tools like dbt
- Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver trusted datasets
- Implement data quality checks and monitoring to ensure accuracy and consistency of data
- Optimize data warehouse performance and query efficiency
Tools & technology
Average salary
Job outlook
ExcellentNew job opportunities are highly likely. Demand significantly outpaces supply in most markets.
Education & training
Bachelor's degree in Computer Science, Data Science, Statistics, or a related quantitative field. Strong practical experience with SQL and data modeling is essential.
Career pathways
WHERE YOU COULD GO
CURRENT ROLE
Analytics Engineer
Data & AI
ADJACENT MOVES
STARTING POINTS
Who thrives here
Interest profile
conventional · CIE
Individuals who enjoy structuring complex information, solving technical problems, and driving tangible outcomes through systematic processes tend to excel in this role.
Personality characteristics
Curious
Enjoys exploring new data technologies and optimizing existing systems to improve data utility.
Methodical
Highly focused on data accuracy, reliability, and structured processes to build dependable data assets.
Reserved
Prefers deep analytical work and technical problem-solving over extensive social interaction.
Analytical
Thrives on breaking down complex data challenges into manageable parts and identifying root causes.
Calm under pressure
Maintains composure and focus when troubleshooting data issues or dealing with unexpected complexities.
Best for
- Individuals who enjoy transforming messy, raw data into clean, usable formats.
- Those who thrive on technical challenges and building robust, scalable data infrastructure.
- People who appreciate the direct impact of reliable data on business decisions and organizational efficiency.
Watch out for
- Requires meticulous attention to detail; errors in data pipelines can have widespread impact on reporting and analytics.
- Can involve troubleshooting complex data issues under pressure, requiring resilience and problem-solving skills.
A week in the life
A representative working week for a Analytics Engineer — where the deep work, meetings, and admin actually land.
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