Data and Operations Engineer

RemoteStar; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

RemoteStar is seeking a Staff/Principal Data and Operations Engineer to lead the design, scalability, and reliability of core data infrastructure and operational systems. You will operate as a hands‑on builder and a strategic leader, mentoring engineers and setting technical direction across the org.

You’ll own end‑to‑end data pipelines, operational excellence practices, and collaboration with Product, Data Science, and Infrastructure to scale data platforms and tooling with the business.

Qualifications

• 8+ years of experience in data engineering, platform engineering, or infra/ops with Staff/Principal scope.
• 4+ years in fintech.
• Deep expertise with distributed data systems (Spark, Kafka, Airflow, dbt) and cloud data warehousing (Snowflake, BigQuery, Redshift).
• Proficient in Python, SQL, and at least one systems language (Go/Java/Scala).

Responsibilities

• Architect, build, and scale data pipelines and infrastructure supporting analytics, ML, and product use cases.
• Own operational reliability — uptime, observability, incident response, and on‑call practices for data and platform systems.
• Set technical direction and best practices for data engineering and operations across the company.
• Partner with Product, Data Science, and Infrastructure to translate business needs into scalable solutions.
• Drive automation initiatives to reduce manual operational overhead.
• Mentor engineers and provide technical leadership across teams.
• Lead architecture reviews, design docs, and tech decision-making for high‑impact systems.
• Identify and resolve systemic bottlenecks in data quality, pipeline performance, and operational workflows.

Skills

Python

SQL

Go/Java/Scala

Tools

Spark

Kafka

Airflow

dbt

Job description

Data and Operations Engineer — Staff/Principal Lead

About the Role

Looking for a Staff/Principal-level Data and Operations Engineer to lead the design, scalability, and reliability of our core data infrastructure and operational systems. This is a senior technical leadership role for someone who can operate as both a hands‑on builder and a force multiplier — setting technical direction, mentoring engineers, and partnering closely with cross‑functional teams to ensure our data platforms and operational tooling scale with the business.

You’ll own critical systems end‑to‑end: from data pipeline architecture to operational excellence practices (monitoring, incident response, automation), and you’ll be a key voice in shaping engineering standards across the org.

What You’ll Do

• Architect, build, and scale data pipelines and infrastructure supporting analytics, ML, and product use cases
• Own operational reliability — uptime, observability, incident response, and on‑call practices for data and platform systems
• Set technical direction and best practices for data engineering and operations across the company
• Partner with Product, Data Science, and Infrastructure teams to translate business needs into scalable technical solutions
• Drive automation initiatives to reduce manual operational overhead
• Mentor and provide technical leadership to engineers at all levels; act as a force multiplier across teams
• Lead architecture reviews, design docs, and technical decision‑making for high‑impact systems
• Identify and resolve systemic bottlenecks in data quality, pipeline performance, and operational workflows

What We’re Looking For

• 8+ years of experience in data engineering, platform engineering, or infrastructure/operations roles, with demonstrated Staff/Principal-level scope
• 4+ years in fintech
• Deep expertise in distributed data systems (e.g., Spark, Kafka, Airflow, dbt) and cloud data warehousing (Snowflake, BigQuery, Redshift)
• Strong proficiency in Python, SQL, and at least one systems language (Go, Java, or Scala)
• Proven experience with cloud infrastructure (AWS, GCP, or Azure) and infrastructure-as-code (Terraform)
• Track record of leading large‑scale technical initiatives with cross‑functional stakeholders
• Strong operational mindset — experience with observability tooling (Datadog, Grafana, Prometheus), incident management, and building resilient systems
• Excellent communication skills and experience mentoring senior engineers
• Comfortable operating with high autonomy and ambiguity in a fast‑paced environment