Sr. Software Engineer, Data Analytics Engineering

Role overview

A senior engineer is needed to improve the quality, reliability, and velocity of data science and product development by building scalable data foundations, analytics tooling, and analysis pipelines. The work enables trusted, self-service access to datasets, insights, and metric definitions across cross-functional teams and involves close partnership with Product, Engineering, Data Science, Data Engineering, and Business Intelligence.

Responsibilities

- Develop and document practical instrumentation and experimentation standards, partnering with product engineering teams to apply them to priority work. - Build and improve scalable analysis pipelines and tooling that produce reliable insights at scale and strengthen shared understanding of key data structures and metrics. - Create tools and processes that let Data Scientists and Engineers independently access trusted datasets, insights, and metric definitions. - Identify data quality and discoverability gaps, advocate for targeted improvements, and contribute to reliable, well-governed data practices. - Maintain clear documentation for tools, datasets, metrics, and operating practices to make team data assets easier to use. - Partner with cross-functional teams to communicate actionable insights and inform product improvements. - Use AI to accelerate analysis, prototyping, and iteration, while applying judgment and verification to ensure correctness, quality, and responsible use.

Requirements

- 4+ years delivering analytics engineering or data solutions in a fast-paced, data-driven environment. - Experience using SQL and Python, R, or a comparable language with large, high-dimensional datasets, including nested data structures, window functions, query optimization, and data partitioning. - Experience building and operating data workflows, including workflow orchestration, ETL/ELT pipelines, and DAG dependencies across complex datasets. - Track record of translating open-ended partner needs into clear, impactful technical objectives and collaborating across Product, Engineering, Data Science, Data Engineering, and Business Intelligence teams. - Demonstrated ability to use AI to improve speed and quality in day-to-day engineering workflows. - Strong record of critically evaluating and verifying AI-assisted work through testing, data validation, source-checking, or peer review. - High integrity and ownership: protecting sensitive data, avoiding over-reliance on AI, and remaining accountable for final decisions and deliverables. - Bachelor's degree in a relevant field such as Computer Science, Statistics, Mathematics, or a related discipline, or equivalent experience.

Benefits and work setup

This is a remote-eligible role that requires in-person collaboration 1–2 times per month, so candidates can be situated anywhere in the country. The position is not eligible for relocation assistance. The annual base salary range is $183,040–$320,320 USD, and the role is also eligible for equity.