Senior Analytics Engineer

Salary

The estimated base salary range for this role is $106,000 - $136,000.

We’re looking for a Senior Data Analytics Engineer to join Snowflake's Support Data Foundations team. In this role, you will be a driving force behind our Support data analytics initiatives, responsible for turning raw data into valuable insights that empower our business. Collaborating with cross-functional teams, you will leverage your data expertise to create maintainable data solutions that enable our leaders to make informed decisions and unlock new opportunities.

As a Senior Data Analytics Engineer at Snowflake you will:

Data Transformation and Analysis:

Design, develop, and maintain performant data pipelines for collecting, processing, and transforming data from various sources into a structured format
Assemble large, complex data sets that meet functional / non-functional business requirements
Provide clean data sets to end users, modeling data in a way that empowers end users to answer their own questions
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Apply software engineering best practices to analytics code (e.g. version control, testing, continuous integration)
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics

Performance Optimization:

Identify and address performance bottlenecks in data processing, analytics, and reporting to ensure efficient and responsive user experiences
Continuously refine and optimize data pipelines for speed, accuracy, and scalability

Data Governance and Security:

Ensure data privacy and security by designing and implementing access controls in compliance with data protection regulations
Collaborate with the security team to identify and mitigate potential risks related to data handling

Data Management:

Maintain data documentation and definitions
Interface with data stewards to ensure metadata is trustworthy and current

Our ideal candidate will have:

Bachelor or Master degree in Analytics, Computer Science, Mathematics, Management Information Systems or similar quantitative discipline
5+ years of experience with SQL, including exposure to Data Manipulation Language (DML) and Data Definition Language (DDL) statements. Advanced proficiency in writing Data Query Language (DQL) statements, with experience using common table expressions and window functions
Experience using dbt (data build tool), including designing and implementing dbt macros
Experience with one or more common data analysis languages (Python, R, Spark) and associated libraries/toolkits such as NumPy, pandas, tidyverse
Experience building ELT processes using tools like Airflow, SQL Tasks & Stored Procedures
Experience with containerization, including Docker, Kubernetes
Proficiency with Git, bash, and command line
Familiarity with metadata management and data catalog tools (e.g. Alation, Select Star)
Passion for designing efficient, modular, and maintainable systems
Attention to detail without losing sight of the bigger picture
Experience collaborating with the business to translate goals into technical specifications and understand when trade-offs must be made.
Experience and interest in problem formulation based on relatively abstract information and evaluating all possible solutions
Experience performing root cause analysis on internal / external data and processes to answer specific business questions and identify opportunities for improvement
Comfortable working with semi-structured datasets
Proven passion for building and learning: open source contributions, pet projects, self-education, Stack Overflow

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