Senior Analytics Engineer

Roles & Responsibilities

We are seeking a highly motivated Senior Analytics Engineer to design and scale a robust analytics platform that delivers impactful insights across key domains, such as Subscription, Growth, Identity, Retention, Content, and Product Analytics. As a Staff Analytics Engineer, you will lead efforts to transform raw data into meaningful and actionable insights by building and maintaining a reliable and scalable analytics data infrastructure.

Your work will directly support analysts, data scientists, and business stakeholders by ensuring data pipelines, models, and metrics are efficient, accurate, and accessible. This role is critical to driving a data-driven culture and enabling teams to make informed decisions.

Architect and manage data pipelines using Databricks notebooks and Apache Spark, focusing on performance and efficiency.

Troubleshoot and optimize Spark applications for handling large, complex datasets.

Develop robust data transformations, data integrations, and automation scripts in SQL and Python.

Implement best practices for code modularity, testing, and deployment within the analytics ecosystem.

Work closely with Data Engineers, Analysts, and other stakeholders to understand data needs and deliver effective solutions.

Provide clear documentation and training to ensure best practices are followed across the organization.

Partner with cross-functional teams to understand evolving data needs and propose innovative solutions.

Contribute to a culture of continuous improvement by evaluating and implementing emerging technologies and approaches.

What to Bring:

Bachelors degree in computer science, business analytics or similar discipline.

5-7+ years of experience in analytics engineering, data engineering, or a related field.

Proficiency in SQL, Spark and ETL/ELT tools (e.g., dbt, Airflow)

Strong Python (or similar) scripting skills for automation and data manipulation.

Hands-on experience with Databricks and Apache Spark, including Spark tuning and cluster management.

Strong analytical and problem-solving abilities to address complex data challenges.

Excellent communication skills to work with both technical and non-technical stakeholders.