Senior Data Analytics Engineer
MariaDB plc
| Company | MariaDB plc |
| Category | Engineering |
| Location | Remote - Bulgaria |
| Remote | Remote |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 1 Apr 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
MariaDB is making a big impact on the world. Whether you’re checking your bank account, buying a coffee, shopping online, making a phone call, listening to music, taking out a loan or ordering takeout – MariaDB is the backbone of applications used everyday. Companies small and large, including 75% of the Fortune 500, run MariaDB, touching the lives of billions of people. With massive reach through Linux distributions, enterprise deployments and public clouds, MariaDB is uniquely positioned as the leading database for modern application development.
About the Role
We're looking for a Senior Data Analytics Engineer who lives and breathes data-someone who combines strong engineering skills with analytical depth. You'll join a small, high-impact team where you don't just analyze data, you build the systems and pipelines that make analytics possible. This isn't a dashboards-and-decks role-you'll engineer solutions across the full analytics stack, from designing reliable data pipelines in BigQuery and MariaDB to building internal tools and APIs that put insights into the hands of the business.
Day to day, you'll write sophisticated SQL in BigQuery and MariaDB, architect and build automation and tooling in Python and FastAPI, and use AI-powered development tools like Windsurf, Gemini, and Claude as a core part of how you work. You need to understand data architecture deeply-how information flows from source systems through pipelines into the warehouse, how schemas are designed, and how to build infrastructure that scales and stays maintainable.
Communication is a big part of this role. You'll work closely with stakeholders across the business, translating complex data into clear, actionable insights. But equally important is your ability to engineer robust, repeatable solutions-not one-off analyses. We need someone who can own their domain end-to-end: define the right questions, build the data infrastructure, deliver the analysis, and present it in a way that drives decisions. If you're self-sufficient, ambitious, always looking to improve, and you have a GitHub profile that shows what you're capable of-we want to talk to you.
Key Responsibilities
Design, build, and maintain analytical pipelines and reporting solutions on BigQuery and MariaDB
Write sophisticated, performant SQL to extract insights from large-scale datasets
Leverage AI and machine learning features to augment analytics workflows and deliver smarter outputs
Use AI-powered development tools (Windsurf, Gemini, Claude, Cursor) to accelerate your workflow and deliver at a higher level
Develop internal tooling and automation using Python, FastAPI, and modern frameworks
Communicate findings clearly to technical and non-technical stakeholders-translate data into action
Understand and document data architecture, lineage, and how information flows across systems
Collaborate on business process analysis and process design improvements driven by data
Proactively identify opportunities for deeper analysis, better tooling, and operational improvements
Requirements & Qualifications
7+ years of professional experience in data analytics engineering, data engineering, or a related field
Expert-level SQL - you think in joins, window functions, and CTEs; BigQuery and MariaDB experience strongly preferred
Strong Python and/or JavaScript skills - comfortable building pipelines, internal tools, APIs, and automation; not just scripts
js experience - ability to build data-facing web applications and internal dashboards
Deep understanding of data architecture - how databases are structured, how data flows, how schemas evolve
Hands-on experience with AI/ML - you stay current with the latest capabilities (LLMs, generative AI, embeddings) and know how to apply them practically
Proficiency with AI-powered development tools - Windsurf, Gemini, Claude, Cursor, or similar; you use AI to multiply your output, not as a crutch
Excellent
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