Senior Analytics / Data Science Engineer
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Protocol Intelligence
Data-driven signals on your job's competitivenessMid-level, popular data role with some Snowflake specialization reduces but doesn't eliminate applicant density.
Data engineering skills transferable, but Snowflake and analytics specialization limit cross-industry portability.
Explicit 5-8 years requirement plus mandatory Snowflake, SQL, and analytics engineering skills increases selectivity.
Job Description
Structured overview of role & requirementsAbout This Role
Build and own data infrastructure for analytics and machine learning workflows ensuring data accuracy and performance.
Deliver production-grade data solutions in collaboration with data science, engineering, and business teams.
Drive decisions by providing reliable, optimized data environments with attention to cost and quality.
Minimum Requirements
5+ years of experience in analytics engineering, data engineering, or equivalent technical role.
Strong hands-on SQL skills with deep Snowflake experience including performance tuning and warehouse management.
Proficiency in Python for data tasks (pandas, NumPy, scripting, and testing).
Solid foundation in statistics: distributions, sampling, hypothesis testing, regression, and confidence intervals.
Ideal Candidate Profile
Experience owning end-to-end data outcomes and frameworks for data quality and accuracy, not just task completion.
Comfortable working across data engineering and data science workflows with understanding of feature engineering and model evaluation.
Proactive ownership approach with focus on investigation, continuous improvement, and delivering production-grade solutions.