Senior Data Ops Engineer (Self-Hosted, Flexible)

digitalextremes; United States; Remote; USD 70,000 - 81,000; Full time

Job summary

digitalextremes is seeking a senior data platform engineer to lead improvements to a self-hosted database and data warehousing stack. You will combine hands-on operations with architecture recommendations and project delivery.

You will build and tune pipelines, manage PostgreSQL and MongoDB, mentor teammates, and collaborate with data scientists and analysts to translate data needs into scalable solutions.

Qualifications

• Five+ years of industry experience with large codebases.
• Experience managing self-hosted PostgreSQL, MongoDB, or similar databases.
• Strong SQL skills in Linux/Unix environments.
• Hands-on experience with ETL orchestration tools such as Dagster or Airflow.
• Knowledge of data warehousing and relational data modeling.
• Experience leading projects and mentoring teams.

Responsibilities

• Maintain and tune database systems, including upgrades, monitoring, performance improvements, and hardware changes.
• Build and operate pipelines for data ingestion and processing, integrating sources while preserving data quality.
• Manage self-hosted databases for large-scale analysis and warehousing workloads.
• Review database architecture and recommend changes to support current needs and growth.
• Work with data scientists, analysts, and other teams to translate data needs into scalable solutions.
• Lead initiatives across teams by setting timelines, tracking progress, and supporting delivery; mentor colleagues and share knowledge.

Skills

SQL

Linux/Unix

ETL tools

Data warehousing

Team leadership

Mentoring

Tools

Dagster

Airflow

PostgreSQL

MongoDB

Job description

digitalextremes is seeking a senior data platform engineer to lead improvements to a self-hosted database and data warehousing stack. You will combine hands-on operations with architecture recommendations and project delivery.

You will build and tune pipelines, manage PostgreSQL and MongoDB, mentor teammates, and collaborate with data scientists and analysts to translate data needs into scalable solutions.