Senior Data Engineer — Remote, Lakehouse & MLOps

Agile Resources, Inc.; Orlando (FL); Remote; USD 83,000 - 96,000; Full time

Benefits offered by this job

Medical

Dental

Vision

Job summary

Agile Resources, Inc. seeks a Sr. Data Engineer to lead the evolution of a global data ecosystem. You will own production-grade data pipelines, enable LLM-ready data, and drive cloud-scale architectures in a fully remote role.

You will design secure data platforms, work across multi-cloud environments, and partner with cross-functional teams to deliver scalable, enterprise-ready solutions. Strong Python/SQL, Spark, and MLOps experience are required.

Qualifications

• 7+ years of sophisticated data engineering experience.
• Proficient in Python and SQL with ML lifecycle management.
• Expertise in Spark tuning, partitioning, and cloud infrastructure.
• Experience designing secure, ACID-compliant storage layers and unified cataloging tools.
• Familiarity with event-driven architectures (e.g., Kafka) and CI/CD pipelines.

Responsibilities

• Architect and optimize high-throughput distributed computing frameworks and Lakehouse structures.
• Build production-grade features and pipelines for LLMs and ML models.
• Create automated ingestion across multi-cloud with streaming and batch processing.
• Ensure data quality, cataloging, and access controls while optimizing costs.
• Collaborate with leadership and operations to translate goals into scalable technical solutions.

Skills

Spark tuning

Partitioning

Cloud infrastructure

Python

SQL

ML lifecycle

LLM integrations

Data governance

Kafka

CI/CD

IaC

Tools

Unity Catalog

Delta Lake

Lakehouse

Kafka

Apache Spark

Databricks

MLflow

Job description

Agile Resources, Inc. seeks a Sr. Data Engineer to lead the evolution of a global data ecosystem. You will own production-grade data pipelines, enable LLM-ready data, and drive cloud-scale architectures in a fully remote role.

You will design secure data platforms, work across multi-cloud environments, and partner with cross-functional teams to deliver scalable, enterprise-ready solutions. Strong Python/SQL, Spark, and MLOps experience are required.