Overview

We are seeking a highly skilled Python Data Engineer with expertise in data

engineering, cloud platforms, and cost optimization. The ideal candidate will design and

optimize ETL/ELT pipelines, work with cloud billing datasets, and integrate analytics into

DevOps workflows.

Required Qualifications

48+ years of Python development experience.

Strong experience with data engineering, especially ETL/ELT pipelines.

Experience working with AWS, Azure, or GCP usage & billing datasets.

Hands-on experience with pandas, NumPy, PySpark, or similar data processing

frameworks.

Familiarity with Kubernetes, cloud compute primitives, and distributed systems.

Experience building dashboards or integrating with BI tools (e.g., Grafana, Datadog,

custom internal tools).

Strong understanding of cloud resource utilization metrics and cost drivers.

Ability to work in a fast-paced, execution-driven environment.

Preferred Qualifications

Prior FinOps or cloud cost optimization experience.

Familiarity with Elasticsearch/OpenSearch, Redis, Cassandra/Keyspaces, Kafka,

and other backend infra.

Prior experience in a B2B SaaS environment with large-scale microservices.

Experience integrating automation/analytics into DevOps workflows.

Strong knowledge of time-series analysis and anomaly detection.

Key Responsibilities

Design and maintain scalable ETL/ELT pipelines for cloud billing and usage data.

Develop Python-based solutions for data processing and analytics.

Collaborate with DevOps teams to integrate cost optimization tools into workflows.

Data Engineer