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# Senior Software Engineer

- **Company:** Akamai Technologies
- **Location:** Boston, MA, United States
- **Experience:** Expert
- **Salary:** $121,400.0 - $218,600.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Airflow, Amazon Web Services, Apache HTTP Server, Microsoft Azure, Cloud Computing, Computer Programming, Data Transmissions, Information Engineering, Python (Programming Language), Query Optimization, Akamai, SQL Databases, Google Cloud, Apache Spark, Data Lakes, Information Technology, Apache Flink, Data Lakehouse, Data Pipelines, Docker
- **Published:** October 30, 2026
- **Apply:** https://dejobs.org/x/x/FFC4B0C91379427BB0B24B7C9A4F8415/job/

## About the Role

* Have 6+ years of software/data engineering experience, with a Bachelor's degree in Computer Science or a related field (or equivalent experience)
 * Demonstrate great programming skills in Python; ideally experience in Java or Scala
 * Have hands-on experience building large-scale pipelines with a modern data framework such as Apache Spark or Apache Flink
 * Have production experience orchestrating pipelines with Apache Airflow
 * Possess deep SQL experience: complex joins, window functions, query tuning, and data modeling for analytics
 * Have experience building or running a data lakehouse (e.g., Delta Lake, Apache Iceberg or Apache Hudi on object storage)
 * Have experience with at least one public cloud (AWS, GCP, Azure )

## Description

As a Senior Software Engineer, you will be responsible for:

 * Designing, building and operating batch and streaming pipelines that ingest usage events from Akamai Cloud compute services at high volume
 * Building metering/rating logic:aggregate raw usage into billable units(instance hours, GPU hours, data transfer, storage, inference tokens) and apply rate cards/contract terms
 * Developing/maintaining a data lakehouse (open table formats on object storage) as the source of truth for usage and billing data
 * Orchestrating workflows with Apache Airflow, including backfills, late-arriving data, retries and SLA monitoring
 * Writing production-grade Python and Spark or Flink jobs, packaged and deployed with Docker
 * Building reconciliation/data-quality checks so every billed unit traces back to its source usage, with audit trails finance can rely on
 * Writing clean, tested, well-documented code; review others' work and raise the team's engineering standards