Remote Staff Data Engineer — Lead Scalable Data Platform

Experity; Nashville (TN); Remote; USD 141,000 - 190,000; Full time

Benefits offered by this job

Medical coverage

Dental/Vision

Ownership program

PTO

Career development

Team events

401(k) match

Remote option

Job summary

Experity seeks an accomplished Data Engineer to lead architecture and hands-on delivery of scalable data pipelines and platform services. You will define integration patterns, design governed data models, and produce production-quality code in Python and SQL for analytics, reporting, and AI/ML.

You will drive CI/CD, DataOps, observability, and cost efficiency, mentoring engineers and collaborating with data scientists to enable AI-ready data access and reliable feature pipelines.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related technical field.
• 8+ years of experience building and operating production-grade data platforms with ownership of complex systems.
• Expert proficiency in Python and SQL with strong software design, testing, debugging, and code review practices.
• Deep hands-on experience with Snowflake, including data modeling, query optimization, performance, and cost management.
• Experience architecting CDC, Kafka, Flink, or comparable distributed event and streaming solutions.
• Strong experience with AWS (S3, Lambda, Glue, Kinesis).
• Proven experience designing high-volume batch and near-real-time ETL/ELT architectures and reusable analytical data models.
• Experience with orchestration technologies such as Airflow.

Responsibilities

• Lead the architecture and hands-on delivery of scalable batch and near-real-time ETL/ELT pipelines and data platform services.
• Define robust integration patterns for databases, APIs, applications, CDC/event streams, and external sources.
• Design reusable, governed data models and semantic-ready datasets for analytics, reporting, and AI/ML.
• Write production-quality code in Python and SQL and tackle complex transformation challenges.
• Drive architectural decisions for scalability, availability, resiliency, and cost efficiency.
• Define reusable frameworks, libraries, and reference architectures used across data engineering teams.
• Advance automated testing, CI/CD, Infrastructure as Code, and DataOps standards; improve developer workflows.
• Establish observability, data freshness, SLAs, alerting, and automated recovery for critical pipelines.
• Lead production issue resolution, cross-system RCA, and preventive architectural improvements.
• Improve Snowflake and cloud compute efficiency, query performance, and storage costs.
• Lead cross-team design reviews and mentor engineers.
• Partner with Data Scientists on reliable feature pipelines and governance for AI-ready data access.
• Translate product needs into phased delivery plans and measurable technical outcomes.
• Communicate architectural tradeoffs and risks clearly to stakeholders.

Skills

Python

SQL

Data modeling

Data architecture

Mentorship

Cross-team collaboration

Problem solving

Education

Bachelor's or Master's in CS/Engineering/Info Systems

Tools

Snowflake

Python

SQL

Kafka

Flink

AWS

Airflow

Docker

Kubernetes

Terraform

CloudFormation

dbt

Job description

Experity seeks an accomplished Data Engineer to lead architecture and hands-on delivery of scalable data pipelines and platform services. You will define integration patterns, design governed data models, and produce production-quality code in Python and SQL for analytics, reporting, and AI/ML.

You will drive CI/CD, DataOps, observability, and cost efficiency, mentoring engineers and collaborating with data scientists to enable AI-ready data access and reliable feature pipelines.