Company
Technology
SeniorDataAnalyticsEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Analytics Engineer. Skills: SQL, Python, BigQuery, MariaDB, data architecture. Design, build, and maintain scalable data pipelines and analytics infrastructure. Write advanced SQL queries. Develop internal tools, APIs, and automation workflows. Build and optimize data models. Collaborate with stakeholders. Implement and enhance data quality, monitoring, and reliability frameworks. Leverage AI-powered development tools. Contribute to documentation. Identify opportunities for process i”
What You'll Achieve.
Opportunity to build high-impact data systems at scale
Industry & Context.
problem-solving; analytical thinking; end-to-end
A public GitHub profile demonstrating real-world projects, experimentation, or engineering contributions.
What They're Looking For.
Must Have
7+ years of experience in data engineering, analytics engineering, or a related technical data role. Expert-level SQL skills with hands-on experience in BigQuery and MariaDB. proficiency in Python (or JavaScript) for building data pipelines, APIs, and automation systems. Experience with modern backend frameworks such as FastAPI or similar tools. Hands-on experience with AI/ML concepts, including LLMs, embeddings, or generative AI applications. Familiarity with AI-assisted development tools such as Cursor, Windsurf, Gemini, Claude, or similar platforms. problem-solving and analytical thinking with ability to work independently end-to-end. Excellent communication skills with the ability to explain complex data concepts to non-technical stakeholders. Proven ability to manage multiple priorities in a fast-paced, self-directed environment. A public GitHub profile demonstrating real-world projects, experimentation, or engineering contributions.
What You'll Do.
Design, build, and maintain scalable data pipelines and analytics infrastructure.
Write advanced SQL queries.
Develop internal tools, APIs, and automation workflows.
Build and optimize data models.
Collaborate with stakeholders.
Implement and enhance data quality, monitoring, and reliability frameworks.
Leverage AI-powered development tools.
Contribute to documentation.
Identify opportunities for process improvement, automation, and advanced analytical capabilities.
How You'll Work.
Team & Collaboration
Collaborate with stakeholders to translate business requirements into technical solutions and actionable analytics.
Communication Scope
Excellent communication skills; ability to explain complex data concepts to non-technical stakeholders
Full Job Description
## Accountabilities Design, build, and maintain scalable data pipelines and analytics infrastructure using BigQuery and MariaDB. Write advanced SQL queries to extract, transform, and analyze large-scale datasets for business insights. Develop internal tools, APIs, and automation workflows using Python and modern frameworks such as FastAPI. Build and optimize data models, ensuring clean architecture, maintainable schemas, and efficient data flow across systems. Collaborate with stakeholders to translate business requirements into technical solutions and actionable analytics. Implement and enhance data quality, monitoring, and reliability frameworks across pipelines and systems. Leverage AI-powered development tools (e.g., Claude, Gemini, Windsurf) to improve productivity and solution quality. Contribute to documentation of data architecture, lineage, and system dependencies for transparency and scalability. Identify opportunities for process improvement, automation, and advanced analytical capabilities. Requirements: 7+ years of experience in data engineering, analytics engineering, or a related technical data role. Expert-level SQL skills with hands-on experience in BigQuery and MariaDB. Strong proficiency in Python (or JavaScript) for building data pipelines, APIs, and automation systems. Experience with modern backend frameworks such as FastAPI or similar tools. Deep understanding of data architecture, including schema design, data modeling, and pipeline orchestration. Hands-on experience with AI/ML concepts, including LLMs, embeddings, or generative AI applications. Familiarity with AI-assisted development tools such as Cursor, Windsurf, Gemini, Claude, or similar platforms. Strong problem-solving and analytical thinking with ability to work independently end-to-end. Excellent communication skills with the ability to explain complex data concepts to non-technical stakeholders. Proven ability to manage multiple priorities in a fast-paced, self-directed environment
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