Senior Analytics Engineer

Responsibilities

• Partner with Data Scientists and business stakeholders to understand analytical needs and translate them into robust data infrastructure and workflows for the global Analytics team.
• Collaborate with the Data Engineering team to design, develop and maintain scalable data models and pipelines.
• Monitor performance and optimize data systems for high performance and reliability.
• Collaborate with the Data Integrity team to build a Data Quality Framework that ensures production data meets SLAs for key stakeholders and business processes.
• Perform timely Root Cause Analysis to troubleshoot data-related issues; assist in implementation of code and process fixes.
• Provide thought leadership and collaborate with other team members to continue to scale our architecture to evolve for the needs of tomorrow.
• Contribute to the establishment of best practices including code standards, version control, documentation, testing, and review processes.
• Develop and support CI/CD processes using Terraform, Github, TeamCity, Octopus, etc.
• Define and implement monitoring and alerting policies for data solutions.

Requirements

• 5+ years of experience in analytics engineering or data engineering with proficiency in Python and PySpark.
• 5+ years of hands-on experience in using advanced SQL queries (analytical functions).
• Bachelor’s degree or equivalent in an engineering or technical field such as Computer Science, Mathematics, Statistics, or strong quantitative and software background.
• Proven track record in building, monitoring, and optimizing large-scale data systems and analytics infrastructure.
• Experience working in Databricks & Azure environment (or other cloud equivalents).
• Experience working with pipeline scheduling tools such as Airflow & Astronomer.
• Experience working with CI/CD tools such as TeamCity, Terraform, Github, Octopus.
• Ability to push the frontier of technology and freely pursue better alternatives.

Pluses

• Knowledge of software coding practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations.
• Streaming or NRT modeling experience.
• Passion for technical mentorship.