Senior Data Engineer (Freelance - all genders)
About this role
Description
At Alfadocs, we're on a mission to transform healthcare. Our software platform makes the daily lives of medical practices and patients easier by streamlining practice management and patient relationships. With our all-in-one, cloud-based solution, healthcare professionals can focus more on care and less on administration.
We take pride in our responsibility to deliver high-performance solutions while fostering a collaborative and respectful environment where everyone's contributions are valued. We're driven by a shared passion to make a lasting impact on the healthcare industry, creating a space where both our team and our customers thrive.
As our Senior Data Engineer (Freelance, all genders), you'll be the first dedicated data professional at Alfadocs, reporting directly to the CEO. You'll take full ownership of building our data infrastructure and transforming raw data into reliable, actionable business insights.
This is a highly autonomous, hands-on role for an experienced professional who has already built a data warehouse from scratch in a growing company and knows how to balance technical excellence with pragmatic business needs.
We're looking for a long-term freelance collaboration of approximately 10-15 hours per week, with the possibility of a higher initial commitment to accelerate the setup.
Data Infrastructure & ETL: Design, build, and maintain robust ETL/ELT pipelines to consolidate data from multiple sources into a reliable, scalable data infrastructure.
Data Warehouse Architecture: Take ownership of designing and implementing our data warehouse, ensuring data quality, consistency, performance, and scalability.
Data Modeling & Semantic Layer: Develop clear, maintainable data models and a semantic layer that provide a consistent foundation for business reporting and analytics.
Business Intelligence & Analytics: Enable and support our internal teams in creating dashboards, charts, reports, and analyses to drive data-informed decisions.
AI & LLM Integration: Ensure our data warehouse can be securely and effectively accessed through LLM-based solutions, enabling context-aware querying and insights..
Technical Strategy & Ownership: Evaluate our existing setup based on Google BigQuery and Dataform, identify opportunities for improvement, and recommend alternative technologies where they provide clear advantages.
Data Governance & Documentation: Establish best practices for data quality, documentation, access management, and compliance, creating a sustainable foundation for future growth.
Requirements
Experience: Significant professional experience in Data Engineering, with demonstrated experience building a data warehouse from the ground up
ETL/ELT & Data Warehousing: Deep expertise in building reliable data pipelines, integrating diverse data sources, and designing scalable data warehouse architectures.
Data Modeling: Strong knowledge of dimensional modeling, data transformations, and semantic layers that support consistent business metrics and self-service analytics.
Technical Stack: Strong proficiency in SQL and modern cloud data warehousing technologies. Experience with Google BigQuery and Dataform is highly relevant, but we're open to alternative tools and architectures.
AI & LLMs: Practical understanding of how to make structured business data accessible to LLM-based applications, with appropriate attention to data context, accuracy, and security.
Language: Proficient in English (at least C1), both written and spoken.
Nice to Have– SaaS Metrics: Experience with SaaS business models and KPIs, including MRR, ARR, logo churn, revenue churn, LTV, CAC, and related metrics.
Nice to Have – Growth-Stage Companies: Previous experience working with fast-growing SaaS companies, particularly as an early or first dedicated data professional.
Administrative Info
Location: Our offices are in Italy & Germany, but this role is fully remote. Candidates must be based within the European Union
Contract: Freelance / Independent Contractor.
Working Hours: Approximately 10-15 hours per week
Collaboration: Long-term collaboration preferred.
Reporting Line: Directly to the CEO.
Technical Environment: We currently use Google BigQuery and Dataform as our initial data infrastructure, but we're open to evaluating alternative technologies based on your expertise.
Originally posted on Himalayas
