Software Engineer, Stats & Analytics

About the role

This role centers on ownership of data pipelines that ensure analytics remain accurate and timely. You will solve hard distributed system problems while adhering to strict reliability rules. The work involves transforming messy events into trustworthy insights for the business. The StackAdapt Marketing Platform performs 465 billion automated optimizations per second. It connects brand and performance marketing to drive measurable results across the customer journey. The platform orchestrates high-impact campaigns across programmatic advertising and marketing channels. You will own the end to end lifecycle of critical analytics pipelines, from ingestion through to delivery and observability. You will collaborate closely with data product and measurement teams to turn complex requirements into robust data solutions. Your work will directly influence how marketing leaders understand performance and optimize media spend. You will be responsible for ensuring that the data infrastructure remains performant, reliable, and consistent as the platform scales.

Key facts

What you'll do

You will design ingesting pathways that reliably stream events through Kafka and similar messaging systems. Services crafted in Go will power high performance analytics against Redshift, Snowflake, TiDB, and MariaDB. You will orchestrate batch and streaming workloads with Airflow, Trino, and Iceberg for lakehouse analytics. You will implement data delivery patterns that maintain consistency and performance across distributed stores and sub teams. Reviewing search and analytics queries in Elasticsearch will support fast, accurate exploration for business users. You will ship observability improvements that clarify latency, throughput, and error behavior in production systems. Partnering with product and data teams will align analytics contracts and prevent misuse of shared data platforms. You will champion memory efficient code and performance tuning for large data sets to meet strict service level objectives. You will contribute to architectural decisions that shape how data is stored, processed, and served across the organization. You will participate in on call rotations to ensure timely resolution of incidents affecting analytics pipelines.

Requirements

The requirements include 2+ years of experience as a backend engineer focused on scalable services. Strong problem solving skills in data structures, algorithms, and optimization are necessary. Experience with relational databases and or key value stores in production is required. You must have built distributed micro services that remain reliable at scale. You must be proficient in writing clean, maintainable Go code for high throughput services. Strong ownership of reliability, performance, and data consistency is expected in all delivered work. You must be comfortable working in a remote first environment and collaborating effectively across distributed teams. Experience with production grade monitoring and alerting is essential for operational responsibilities. You must be able to interpret complex requirements and translate them into robust technical specifications.

Nice to have

Nice to have experience with data lakehouse tools and real time analytics platforms.

About the company

StackAdapt builds systems that connect advertising data with activation workflows. The team applies probabilistic modeling, causal inference, and simulation to support media planning and measurement.

Applied Machine Learning Scientist roles in Ireland focus on recommendation, forecasting, and uplift modeling. You will work with media datasets, production pipelines, and experimentation frameworks to improve targeting and performance insights.

About StackAdapt

StackAdapt is hiring for Software Engineer, Stats & Analytics. The listing location is Alberta, Canada; British Columbia; Calgary, Alberta, Canada; Canada; Ontario; Toronto; Vancouver.

This Software Engineer, Stats & Analytics opening is posted for Alberta, Canada; British Columbia; Calgary, Alberta, Canada; Canada; Ontario; Toronto; Vancouver.