Senior Analytics Engineer

Role Description As a Senior Analytics Engineer, you’ll work across multiple engineering teams and projects to contribute to the system design, development, integration, and maintenance. You’ll design and build reusable components, frameworks and libraries to support the calibration of ML models and inferencing pipelines, as well as clean, prepare and optimize data for ingestion and consumption. Responsibilities Model raw data into clean, tested, and reusable datasets, making it easier for other stakeholders to view and understand data in a data warehouse or database. Translate user and product requirements into data model requirements to execute against and make critical decisions regarding the business rules and how they’re implemented. Build ETL pipelines that can efficiently process very large datasets. Design, implement and maintain online and offline feature stores to support ML training and inference. Develop and maintain data and design documentation to ensure that everyone on the team uses the same definitions and language and is executing against the same architectural vision. Draft and maintain documents that describe how the data flows from data sources to consumption by visualizing them with directed acyclic graphs (DAGs). Define metrics and implement tests to guarantee data meets operational and analytics needs. Develop and maintain automation, scheduling and monitoring of processes designed to gather data from disparate sources and preparing them for data analysis. Use CI/CD processes throughout the data model development lifecycle to develop higher quality code and data models without disruption to production. Qualifications Over 4 years of hands-on experience in data engineering, analytics, or data science, with a strong focus on supporting data pipelines for machine learning models deployed in production environments. Bachelor’s degree in statistics, mathematics, computer science, software engineering, or related field. Master’s degree is a plus. Proficient in SQL and Python. Practical experience to handle various data orchestration tasks is required. Data modeling: Experience developing data models for specific business processes. Familiarity with common data modeling techniques including Star Schema (Kimball’s), One Big Table (OBT) and Data Vault. Experience with the ML lifecycle is preferred, in particular feature stores. Experience with cloud-based development and infrastructure as code principles. Extensive hands-on experience with tools for building data pipelines like Snowflake, Amazon Redshift, and Google BigQuery; ETL tools like AWS Glue, Talend, or others; Business Intelligence tools like Tableau, Looker, or equivalent. Comfortable with software engineering best practices: version control (git), writing unit testing, code review, and CI/CD. Demonstrates exceptional interpersonal and communication skills, facilitating seamless collaboration throughout the organization. Requirements Proficient in understanding and anticipating stakeholder needs, effectively engaging with key stakeholders to convey the value of analytics initiatives and align them with business objectives. Committed to fostering and maintaining positive, productive relationships with colleagues and customers. Benefits Salary range: 125k – 135k. Application Deadline: The application window for this position is anticipated to close on June 28, 2026.