Data Engineer - Remote

Company : Experis

Location : San Francisco, CA

Posted Date : 7 October 2025

Job Type : Other

Category : Software Development

Occupation : Data Engineer

Job Details

Data Engineer
We're hiring a Data Engineer to design, build, and operate the data pipelines and platform that power analytics and AI/ML use cases. You'll own batch and streaming ingestion, transformation, modeling, and data quality at scale-ensuring our data is reliable, well-governed, cost-efficient, and delivered with strong SLAs. You'll partner closely with product, analytics, and ML teams to turn raw data into trusted, self-serve datasets and features.
Key Responsibilities

Build and operate scalable batch and streaming data pipelines.
Model, document, and publish curated datasets and ML-ready features.
Enforce data quality with automated tests, SLAs, lineage, and monitoring.
Tune storage and queries to optimize performance and cost.
Protect data with robust security, privacy, and compliance controls.
Collaborate with product, analytics, and ML teams and support production systems.

Required Skills and Experience

4-6+ years of production data engineering experience or equivalent.
Advanced SQL and proficiency in at least one general-purpose programming language, with hands-on experience using distributed data processing frameworks.
Proven delivery on a major cloud with a modern warehouse or lakehouse.
Working knowledge of streaming patterns and platforms.
Strong data modeling and fluency with modern file and table formats.
Proficiency in orchestration, CI/CD, and infrastructure as code.
Demonstrated ownership of data quality, observability, and lineage.
BS in CS/Engineering or equivalent and strong communication skills.

Preferred Qualification

Experience building and maintaining feature pipelines and stores for ML.
Familiarity with data catalog, lineage, and data quality toolchains.
Track record enabling self-serve analytics with semantic layers or data build tool.
Experience with containers and Kubernetes in production.
Relevant cloud certifications and SaaS or product analytics domain exposure.
Evidence of mentorship, code reviews, and cross-team technical leadership.

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