Deputy is hiring a
Analytics Engineer

Summary

Join Deputy, a global SaaS workforce management company, as an Analytics Engineer to enhance our data and analytics ecosystem, design scalable data pipelines, and collaborate with cross-functional teams.

Requirements

• 2-3 years of experience in a technical analytics or data engineering role, with a strong background in Computer Science, Information Systems, or a related field
• Expertise in SQL and relational databases, with experience working on data modeling and query authoring
• Skilled in using dbt for data modeling and transformation, with a focus on building efficient data pipelines
• Experience in applying advanced analytics techniques, such as machine learning and predictive modeling, to real-world challenges
• Proficiency in using analytical tools and libraries like Pandas, NumPy, and Scikit-learn for data analysis and model development
• Working knowledge of stream processing and scalable data stores
• Solid understanding of data management principles, governance best practices, and regulatory requirements
• Ability to communicate technical insights to non-technical stakeholders, driving alignment on data initiatives

Responsibilities

• Design and optimize data pipelines and architectures using Databricks Data Warehouse to ensure scalability and reliability for large data volumes
• Collaborate with Data Engineering to build infrastructure for data extraction, transformation, and loading using SQL and AWS big data technologies
• Utilize dbt to create and maintain efficient data models, transforming raw data into actionable insights for key stakeholders
• Develop advanced analytics solutions, including machine learning models and predictive analytics, to support data-driven decision-making
• Work closely with cross-functional teams, including Data Scientists, Engineers, and Product Managers, to deliver data solutions that align with business objectives
• Establish best practices for data quality, governance, and security to maintain the integrity of our data assets
• Provide mentorship and share expertise on analytics and data engineering best practices with team members
• Stay informed on emerging technologies and techniques in data engineering and analytics to drive innovation
• Advocate for data-driven decision-making by promoting the value of data across teams and fostering collaboration

Benefits

• Ownership in the company via Share Options
• Paternity/Maternity Leave Policies
• Flexible Remote-First Work Policy
• Company wide Development & Coaching
• Hackathons
• Awards - "Your Time to Shine & Celebrate Success"
• Social Events & variety of social clubs (Books, LGBT, Games, Sports)
• Mental Health Support
• Munch & Learns