How much do data analytics engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for data analytics engineer in Aurora, IL is $128,605.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $136,300.00 per year, depending on experience, location, and employer.

How do data analytics engineers typically collaborate with data scientists and business stakeholders on projects?

Data Analytics Engineers play a crucial role in bridging the gap between raw data and actionable insights by building, optimizing, and maintaining data pipelines. They often work closely with data scientists to ensure data is clean, accessible, and structured for advanced analytics or machine learning models. Additionally, they collaborate with business stakeholders to understand reporting requirements and ensure that data solutions align with organizational objectives. Regular communication and cross-functional teamwork are essential aspects of this role, as engineers must translate business needs into technical specifications and deliver reliable data products.

What are the key skills and qualifications needed to thrive as a data analytics engineer, and why are they important?

To thrive as a Data Analytics Engineer, you need strong proficiency in data modeling, SQL, and statistical analysis, typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools such as Python, R, Apache Spark, Tableau, and cloud data platforms like AWS or Google BigQuery is essential, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you translate data insights into actionable business solutions. These skills and qualities are crucial for designing robust data pipelines and enabling data-driven decision-making across organizations.

What is the difference between Data Analytics Engineer vs Data Scientist?

Aspect Data Analytics Engineer Data Scientist Credentials Bachelor's or master's in CS, Data Science, or related fields; certifications like Google Data Analytics Bachelor's or master's in CS, Statistics, or related fields; certifications like Certified Data Scientist Work Environment Focus on building data pipelines, dashboards, and analytics tools Focus on statistical modeling, machine learning, and data exploration Employer & Industry Usage Used across tech, finance, healthcare for data infrastructure and analytics Common in research, product development, and advanced analytics teams While both roles work with data, Data Analytics Engineers primarily develop data infrastructure and tools for analysis, whereas Data Scientists focus on statistical modeling and machine learning to generate insights. They often collaborate but have distinct technical focuses.

Aspect	Data Analytics Engineer	Data Scientist
Credentials	Bachelor's or master's in CS, Data Science, or related fields; certifications like Google Data Analytics	Bachelor's or master's in CS, Statistics, or related fields; certifications like Certified Data Scientist
Work Environment	Focus on building data pipelines, dashboards, and analytics tools	Focus on statistical modeling, machine learning, and data exploration
Employer & Industry Usage	Used across tech, finance, healthcare for data infrastructure and analytics	Common in research, product development, and advanced analytics teams

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