Middle / Senior Data Solutions Engineer
New
Source API remote eligibility restrictions: United States
Location: EMEA, CETFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 2+ years of experience
- Required Skills
- PythonSQLJavascriptAirflowRESTful APIsData modelingBigQueryGitHub
Requirements
- 2+ years of experience with good knowledge of SQL, JavaScript (used for automation in the Google ecosystem), and Python.
- Experience with BigQuery or strong general database expertise; Dataform experience is preferred but not mandatory.
- Hands-on experience with Airflow or similar orchestration tools.
- Strong understanding of data architecture, modeling frameworks, and performance optimization.
- Proven track record in automation, data quality improvements, and building internal tools (JS/Python).
- Strong understanding of APIs and BI platform integrations.
- Advanced experience using GitHub for collaborative development.
- Excellent problem-solving, communication, and cross-functional collaboration skills.
- Experience in AdTech is strongly preferred, or interest in the domain or marketing-related education.
Responsibilities
- Design and implement complex automation workflows across BigQuery, BI systems, and other tools.
- Build and maintain operational integrations that connect various tools and systems directly (e.g., ClicData, Slack, Google Sheets, or marketing platforms).
- Lead major incident investigations, conduct root cause analyses, and implement preventive improvements and recovery mechanisms.
- Drive analytical and critical thinking in data initiatives; challenge assumptions and propose innovative solutions.
- Manage version control, code reviews, and collaborative development via GitHub; lead debugging, monitoring, and optimization of automation pipelines.
- Collaborate with the engineering team to ensure automations align with reporting and system needs.
- Write and maintain clean, modular, and scalable code; establish automated testing.
- Develop and maintain comprehensive documentation frameworks; create reusable guides, and ensure transparency across projects.
- Demonstrate exceptional attention to detail and establish team-wide quality standards; contribute to and align data strategies with organizational goals, influencing long-term data roadmap and architecture decisions.
- Mentor junior colleagues.
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