Data and Operations Engineer

The Remote Start Guys LLC
San Francisco, CA, United States
5 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
4 years minimum
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) Airflow Amazon Web Services Microsoft Azure BigQuery Cloud Computing Cloud Database Information Engineering Distributed Data Store Python (Programming Language) Prometheus SQL Databases
+11 more
Datadog Snowflake Grafana Apache Spark Core Data Apache Kafka Operational Systems Data Management Terraform Data Pipelines Amazon Redshift

Job description

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

Requirements

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-functionally 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

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