Software Engineer, Stats & Analytics

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.

The Stats and Analytics team at StackAdapt solves complex distributed system challenges, focusing on scalability, performance, reliability, and data consistency. We leverage a modern tech stack that includes Golang for high-performance services, TiDB for scalable SQL databases, Redshift and Snowflake for data warehousing, Kafka for real-time streaming, Elasticsearch for analytics, and HDFS for distributed storage. The Stats & Analytics team is structured into three sub teams: Data Ingestion, Data Platform and Data Delivery. 

About the Data Ingestion Team:

This team builds and operates the critical infrastructure that serves as the “front door” of StackAdapt’s event flow. We work on large-scale distributed systems focused on scalability, performance, reliability, and data correctness, processing 10+ billion events per day. Our systems power core functions across bidding, reporting, billing, analytics, and machine learning. We design and run low-latency, highly reliable ingestion systems for impressions, clicks, conversions, and third-party signals, ensuring data is accurate and available for downstream teams in real time.

About the Data Platform Team: 

This team is 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.

• Building highly scalable, distributed real-time micro-services primarily written in Go
• Working with large data sets and various databases including Aerospike, Elasticsearch, Redis, ScyllaDB, Redshift, TiDB, MariaDB
• Working with data lakehouse technologies like Apache Iceberg, Apache Trino, and real-time analytics technologies like StarRocks and Clickhouse 
• Build software that utilize messaging queues such as Kafka, SQS, and Kinesis
• Write performance efficient and memory optimized code

• 2+ years of experience as a Backend Software Engineer.
• Very strong problem solving skills in data structures, algorithms, and optimization
• Experience working with relational databases and/or key-value stores
• Experience building scalable micro-services and distributed systems