What you''ll do:
- Partner directly with clients and product teams, translating business problems into technical requirements (and technical solutions back into plain-language insights)
- Design and build end-to-end data pipelines, integrating data from various APIs and databases
- Implement Medallion architecture (Bronze/Silver/Gold) to organize data for analytics and AI
- Build and track ML and data analysis experiments (e.g., using MLflow)
- Use AI tools to accelerate prototyping and reduce repetitive work, while critically validating outputs for production quality
- Collaborate with Product Managers and Designers to turn vague asks like "I want better analytics" into concrete technical specs and dashboard prototypes
- Implement data governance, schema enforcement, and testing to ensure high data quality
What you bring:
- 3+ years of hands-on experience in data engineering and/or data science
- Strong proficiency in Databricks, Spark/PySpark, and Delta Lakehouse architecture
- Expertise in Python, SQL, and PowerBI; experience with Azure tools (Data Factory, Key Vault)
- Solid statistics foundation — experimental design, hypothesis testing, causal inference — applied to real datasets
- Strong data visualization and storytelling skills for technical and non-technical audiences alike
- Experience orchestrating workflows with tools like Databricks Workflows, Airflow, or Azure Data Factory
- Comfort using AI coding tools (copilots, LLMs) with strong judgment on validation and correctness
- Git-based version control experience and comfort navigating ambiguity
- Bachelor''s degree in a technical field or equivalent practical experience
Bonus points:
consulting/professional services background; experience in healthcare or other data-intensive industries; dashboard-building experience with Databricks, Genie, or PowerBI
Rate:
Not specified
Location:
Remote
IR35 Status:
Outside
Remote Status:
Remote
Industry:
Data & Analytics
Seniority Level:
Mid-Level