Title: Staff Data Engineer

Location: Remote (client based in San Francisco Bay Area)

Engagement Type: Contract OR Direct Hire

Compensation: Client would like to convert around 250k + bonus

About the Client

Our client is a high-growth technology company headquartered in the San Francisco Bay Area, operating at the intersection of large-scale data systems, machine learning products and real-time analytics. They are seeking a seasoned Staff Data Engineer who can operate at the platform level, collaborate across teams, and deliver scalable data solutions that serve millions of users.

Role Summary

As a Staff Data Engineer, you will play a pivotal role in designing, building and maintaining the data infrastructure that powers analytics, ML-models, BI and data-driven decision-making. You will partner with data scientists, analytics engineers, software engineers, and business stakeholders to define the roadmap, lead major technical initiatives, and ensure the architecture remains performant, reliable and adaptable for future growth.

Key Responsibilities

Lead the end-to-end design and implementation of data platforms and systems: ingestion, transformation, storage, serving.
Architect and build high-throughput, low-latency data pipelines serving both batch and streaming use-cases.
Establish and enforce best practices for data modeling, data quality, observability, lineage and governance.
Collaborate with other engineering leads to integrate data solutions into product workflows, ML pipelines and user-facing applications.
Mentor and coach other data engineers; contribute to a high-performing team culture.
Evaluate new technologies, tools and patterns (e.g., cloud-native data warehouses, real-time messaging, feature stores) and guide adoption.
Monitor, tune and troubleshoot large-scale systems; drive production readiness, SLAs, failure-handling and resiliency.
Influence roadmap and strategy: translate business/analytics requirements into scalable infrastructure, and anticipate future needs.
Communicate technical design decisions effectively to both engineering and business leadership.

Required Qualifications

8+ years professional experience in data engineering or related roles (platform, analytics, data infrastructure) in high-scale environments.
Deep expertise in both batch and streaming systems (for example: Apache Spark, Kafka, Flink, Kinesis, Beam).
Strong competency in data warehousing, dimensional modeling, OLAP systems, big data architecture.
Experience with cloud platforms (AWS, GCP or Azure) and associated data services (e.g., Redshift, BigQuery, Snowflake, Databricks).
Proficient in one or more programming languages such as Python, Scala, Java.
Excellent SQL skills – working with large, distributed datasets.
Skilled at system design: creating scalable, maintainable, secure and performant data systems.
Proven track record of mentoring engineers and influencing cross-functional teams.
Strong communication skills, ability to present complex ideas simply and drive decisions.
Able to work remotely, and coordinate with a Bay-Area-based team (overlaps in U.S. Pacific Time zone preferred).

Preferred Qualifications

Prior experience with feature stores, ML-data infrastructure or real-time recommendation/analytics engines.
Experience implementing data observability, lineage, governance frameworks.
Familiarity with microservices architecture and real-time data products.
Experience in fast-moving startup or scale-up environments.

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