Senior Software Engineer, Stats & Analytics - Data Platform - Remote

Overview

StackAdapt is the leading technology company that empowers marketers to reach, engage, and convert audiences with precision. With 465 billion automated optimizations per second, the AI-powered StackAdapt Marketing Platform seamlessly connects brand and performance marketing to drive measurable results across the entire customer journey. The most forward-thinking marketers choose StackAdapt to orchestrate high-impact campaigns across programmatic advertising and marketing channels.

We’re seeking a Senior Engineer to join our Stats & Analytics Data Platform team — the group responsible for building and operating the infrastructure that powers data at scale across StackAdapt. Our systems process terabytes of data daily, serving both real-time and batch use cases. The data platform ensures that data is fresh, accurate, and cost-efficient so that analytics, machine learning, and product teams can rely on trustworthy, governed datasets.

What You'll Be Doing:

• Design and build scalable data pipelines, batch jobs, and streaming processes that power analytics and machine learning.
• Implement and optimize data storage systems (warehouses, lakes, analytical databases) with a focus on reliability, lineage, and governance.
• Develop tools and frameworks to support data orchestration, ETL workflows, and big data processing.
• Collaborate with engineers, data scientists, and product managers to align platform capabilities with business needs.
• Ensure data systems meet requirements for quality, scalability, and cost efficiency in cloud environments.
• Contribute to technical discussions, code reviews, and system design sessions.
• Take ownership of features and projects, driving them from concept to production.

What You'll Bring to the Table

• Strong background in software engineering, data engineering and distributed systems, ideally at scale (terabytes+).
• Hands-on experience with modern data warehouses, lakes, and compute/storage technologies (e.g., Snowflake, Pinot, TiDB, Spark, Airflow, Kafka, Trino/Presto).
• Experience designing and building robust ETL pipelines and real-time streaming processes.
• Solid understanding of data governance, lineage, and cost optimization in cloud environments.
• Ability to write clean, maintainable, and performant code in production systems.
• Strong problem-solving skills and ability to collaborate across teams.