Senior Software Engineer ‘ Cloud Data Pi

Stellenbeschreibung:

This is a remote position that could be based anywhere in the United States.

Calix is leading a service provider transformation to deliver a differentiated subscriber experience around the Smart Home and Business, while monetizing their network using role‑based cloud services, telemetry, analytics, automation, and the deployment of software‑driven adaptive networks.

As part of a high‑performing global team, the right candidate will play a significant role as a Calix Cloud Data Engineer involved in architecture design, implementation, and technical leadership in the data ingestion, extraction, and transformation domain.

Responsibilities and Duties

Work closely with Cloud product owners to understand, analyze product requirements and provide feedback.
Architecture design and review of Cloud data pipeline, including data ingestion, extraction, and transformation services.
Implement and enhance support tools for monitoring and acting on data pipeline issues and interpreting trends and patterns.
Technical leadership of software design in meeting requirements of service stability, reliability, scalability, and security.
Guide technical discussions within engineer group and make technical recommendations.
Design review and code review with peer engineers.
Guide testing architecture for large‑scale data ingestion and transformations.
Customer‑facing engineering role in debugging and resolving field issues.

Qualifications

Travel may be required to attend face‑to‑face meetings and Calix sponsored events.
7-10 years of software engineering experience.
4+ years of development experience performing ETL and/or data pipeline implementations.
Organized and goal‑focused, able to deliver in a fast‑paced environment.
Strong understanding of distributed systems and RESTful APIs.
Experience with cloud‑based big data projects (preferably in either AWS or Azure).
Working experience with cloud‑based data warehouses such as Greenplum, Redshift, Azure SQL Data Warehouse, etc.
Hands‑on experience implementing data pipeline infrastructure for real‑time availability of data for applications, BI analytics, and ML pipelines.
Expert level working knowledge of data lake technologies, data storage formats (Parquet, ORC, Avro) and query engines (Athena, Presto, Dremio) and associated concepts for building optimized solutions at scale.
Experience in designing data streaming and event‑based data solutions (Kafka, Kinesis, or similar).
Experience building data pipelines (Flink, Spark, or similar).
Experience designing optimized solutions for large datasets.
Knowledge and experience designing solutions with cloud‑native AWS services (EC2, EMR, RDS, EKS, etc.) as well as deploying alternative solutions for appropriate use cases.
Expert level in one of the following programming languages or similar: Python, Java, Go.