Senior Software Engineer

Akamai•United States,

2h•$121,400 - $218,600

About The Position

The Senior Software Engineer will join Akamai’s Netstats Engineering team within its Data Intelligence team, which operates large-scale usage and billing pipelines for Akamai products. The team turns raw usage from compute instances, GPUs, storage, networking, and AI inference into accurate, auditable billing data. This hands-on role designs, builds, and operates batch and streaming pipelines that ingest high-volume usage events from Akamai Cloud compute services. It develops metering and rating logic to aggregate raw usage into billable units and apply rate cards and contract terms, and helps maintain a data lakehouse on object storage as the source of truth for usage and billing data. The engineer also orchestrates workflows, builds reconciliation and data-quality checks, and writes production-grade code with strong testing and documentation practices.

Requirements

At least 6 years of software or data engineering experience.
Bachelor’s degree in Computer Science or a related field, or equivalent experience.
Strong programming skills in Python.
Hands-on experience building large-scale pipelines with a modern data framework such as Apache Spark or Apache Flink.
Production experience orchestrating pipelines with Apache Airflow.
Deep SQL experience, including complex joins, window functions, query tuning, and data modeling for analytics.
Experience building or running a data lakehouse, such as Delta Lake, Apache Iceberg, or Apache Hudi on object storage.
Experience with at least one public cloud: AWS, GCP, or Azure.

Nice To Haves

Experience with Java or Scala.

Responsibilities

Design, build, and operate batch and streaming pipelines that ingest high-volume usage events from Akamai Cloud compute services.
Build metering and rating logic that aggregates raw usage into billable units, including instance hours, GPU hours, data transfer, storage, and inference tokens, and applies rate cards and contract terms.
Develop and maintain a data lakehouse using open table formats on object storage as the source of truth for usage and billing data.
Orchestrate workflows with Apache Airflow, including backfills, late-arriving data, retries, and SLA monitoring.
Write production-grade Python and Spark or Flink jobs, packaged and deployed with Docker.
Build reconciliation and data-quality checks so billed units trace back to source usage, with audit trails finance teams can rely on.
Write clean, tested, and well-documented code; review others’ work and raise the team’s engineering standards.