Job Type

Full-time

Description

This is a fully remote position, allowing you to work from home or location of record within the U.S. with no in-office requirements. You must be available five days per week during designated work hours. The work arrangement for this role is subject to change based on business needs and individual performance. This may include adjustments to on-site requirements.

Staff Engineer Data

Position Overview

The Staff Data Engineer is a senior technical individual contributor responsible for designing and implementing scalable, resilient data systems that support enterprise reporting and analytics. This role operates with enterprise data platform awareness and provides advisory input into organizational architecture decisions that impact or connect to the data platform. The Staff Data Engineer floats between teams to accelerate ambiguous, high-impact projects, drive reusability through shared patterns and standards, and owns operational health outcomes in the areas they influence.

Primary Responsibilities

The below represents the primary duties of the position, others may be assigned as needed. To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Design, build, and evolve scalable, secure, and resilient data platform capabilities that support enterprise reporting, analytics, and downstream consumers including BI and ML/AI solutions.
• Develop and maintain ELT pipelines, analytical and reporting data models, and curated datasets optimized for reliability, performance, and reuse.
• Write modular, well-architected, maintainable code designed for reuse across teams (shared libraries, templates, reference implementations).
• Apply scalability, reliability, and distributed-systems thinking to production data workloads (idempotency, retries, backpressure, failure isolation, recovery).
• Always think in terms of architecture for your domain and beyond; connect local decisions to platform-wide patterns and downstream consumers.
• Float between teams to accelerate vague or ambiguous initiatives, reduce duplication, and increase reuse through shared capabilities and standards.
• Provide advisory input into organizational and system architecture decisions that impact or integrate with the data platform.
• Identify, advocate for, and complete high-impact coding projects (e.g., refactoring, simplification, platform hardening) that reduce technical debt and increase leverage.
• Own and be accountable for large project features end-to-end, including design, delivery, rollout, reliability, and cost awareness.
• Own health when issues arise or costs spike in areas youre working around/with; lead triage, drive root-cause analysis, and land preventive fixes.
• Proactively identify risks and issues (correctness, reliability, security, cost, delivery); communicate early and mitigate through design and execution.
• Demonstrate attention to quality, performance, and observability by ensuring monitoring, actionable alerts, and practical runbooks for owned areas.
• Establish, influence, and drive adoption of coding standards, data standards, and operational best practices across the data engineering space.
• Contribute to and help evolve data governance and operating models that improve data quality, consistency, and trust.
• Advocate for automation and efficiency across the data engineering workflow (CI/CD, testing, repeatable deployments, documentation, lineage).
• Identify and solve quality problems in others code with actionable review feedback, pairing, and driving follow-through to resolution.
• Maintain a high bar in code reviews and technical design discussions (clarity, correctness, testing, operability, alignment to standards).
• Balance technical complexity with user experience and consumer needs (reporting applications, BI consumers, ML/AI use cases).
• Gain alignment from team-level to org-wide on technical strategy and best practices by influencing through clear proposals, prototypes, and coaching.
• Effectively partner with project stakeholders and leadership to clarify goals, manage tradeoffs, and drive outcomes.
• Serve as a formal technical lead on projects; delegate work effectively by providing context and success criteria, fostering growth and ownership throughout the team.
• Focus on high-priority projects first; explicitly deprioritize lower-value work and communicate tradeoffs clearly.
• Actively mentor or coach all team members, providing feedback to grow hard skills (design, SQL/Python quality) and soft skills (communication, influence).
• Resolve conflict and foster productive discussions; encourage an open and inclusive culture.
• Drive continuous team improvement by turning learnings into updated standards, patterns, and practices.
• Demonstrate significant learning outside of primary team responsibilities and apply it to improve the data platform and team effectiveness.

Education and Experience

• Bachelors degree in Computer Science, Data Engineering, or related discipline or equivalent practical experience.
• 7+ years of experience in data engineering, including ownership of large-scale production data systems and hands-on leadership as a technical lead.
• Strong expertise in cloud architectures, distributed systems, and automation, especially within AWS-based data platforms.
• Deep hands-on experience with reporting and analytics data modeling and ELT pipelines.
• Strong experience with Snowflake, dbt, Python, and SQL with exception-level proficiency.
• Experience with real-time or event-driven data processing (e.g., Kinesis, EventBridge) and orchestration (e.g., MWAA/Airflow).
• Experience enabling a broad set of consumers, from reporting applications and BI to ML/AI solutions built on top of curated data products.
• Proven track record optimizing large-scale data platforms for reliability, performance, and cost.

Physical requirements

• Ability to sit for extended periods: The role requires sitting at a desk or workstation for long periods, typically 7-8 hours a day.
• Use of computer and phone systems: The employee must be able to operate a computer, use phone systems, and type. This includes using multiple software programs and inquiries simultaneously.

The pay range for this position is $117,900 - $168,000/yr; however, base pay offered may vary depending on job-related knowledge, skills, and experience. This position is eligible for a restricted stock unit grant based on individual performance in addition to a full range of benefits outlined here Benefits Link . This information is provided per the relevant state and local pay transparency laws for the location in which this position will be performed. Base pay information is based on market location. Applicants should apply via www.paylocity.com/careers.

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