Senior Analytics Engineer

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🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $125k - $135k / year

⏰ Full Time

🟠 Senior

📊 Analytics Engineer

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HMH

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

📚 Education

🛍️ eCommerce

Education • eCommerce • Professional Development

HMH is an educational company that specializes in providing comprehensive curriculum and assessment solutions across a wide spectrum of subjects. They offer programs and resources for literacy, mathematics, science, social studies, and social-emotional learning for K-12 students. Additionally, HMH focuses on professional development for educators to enhance instructional strategies and improve student outcomes.

📋 Description

• Model raw data into clean, tested, and reusable datasets. • Since data models are created around business needs, the job of analytics engineers is to define the rules and requirements for the formats and attributes of data. • Translate user and product requirements into data model requirements. • Builds 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 ensuring all team members are 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. • Responsible for implementing data quality standards across the organization. • 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.

🎯 Requirements

• 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. • 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.