{"id":738783,"url":"https://alion.io/job/harborcompliance-staff-data-engineer","title":"Staff Data Engineer","company":{"id":673747,"name":"Harbor Compliance","domain":"harborcompliance.com","url":"https://alion.io/company/harborcompliance","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Rippling","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":140000,"max_usd":253000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":132},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Claude","optional":false},{"name":"Claude Code","optional":false},{"name":"Copilot","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Embeddings","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Fivetran","optional":false},{"name":"Flink","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Looker","optional":false},{"name":"Milvus","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"Weaviate","optional":false},{"name":"PostgreSQL","optional":true}],"status":"closed","first_seen_at":"2026-08-26T14:06:26Z","employer_posted_date":"2026-08-26","last_verified_at":"2026-11-04T19:50:27Z","board_verified":false,"closed_at":"2026-11-04T19:50:27Z","days_open":70,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":70},"description":"Great Place to Work® Certified | USA\nHarbor Compliance is a leading technology platform for entity compliance, helping more than 80,000 businesses and nonprofits manage licensing, tax registration, and legal entity requirements nationwide. Founded in 2012 and recognized repeatedly by the Inc. 5000 and Deloitte Technology Fast 500, we've grown through five strategic acquisitions - and are now backed by a 2026 majority growth investment from Bregal Sagemount to accelerate product, AI, and customer experience. We're a passionate team making compliance simpler and smarter for every organization we serve.\nHarbor Compliance is building its first end-to-end data platform - unifying fragmented data from HubSpot, financial systems, and HRIS into a single, AI-augmented source of truth for executive decision-making. As Staff Data Engineer, you'll be a foundational technical hire, working closely with the Sr. Director of Data Platform & Analytics to design and build the real-time, AI-ready data infrastructure that powers this platform. This is a hands-on role for someone who wants to build from the ground up, not maintain what already exists.\nKey Responsibilities\nDesign, build, and own near real-time data pipelines (CDC, streaming ingestion, event-driven architectures) as the backbone of the platform's data flow\nEvaluate, implement, and maintain vector database infrastructure and embedding pipelines to support AI-augmented use cases (semantic search, retrieval-augmented generation, AI agents acting on company data).\nDesign and build ELT/ETL pipelines ingesting data from our platform, financial platforms, CRM (HubSpot) and HRIS, feeding both real-time and batch use cases.\nPartner with the Sr. Director to architect the underlying warehouse/lakehouse as a supporting system of record - the storage layer beneath the streaming and AI infrastructure.\nBuild lightweight transformation layers (e.g., dbt) as needed to enable our Analytics Engineering team translate raw data into business-ready datasets aligned to core metrics like ARR, CAC, and churn.\nOwn pipeline reliability and observability - monitoring, automated failure alerting, and lineage tracking across both streaming and batch pipelines.\nBuild the technical foundation for self-service and AI-powered reporting, partnering with BI, Product & Engineering stakeholders on recurring executive and departmental reports.\nImplement data governance practices, including documentation standards and access controls.\nPartner cross-functionally with Finance, Marketing, Customer Success, and Operations to translate data needs into reliable, low-latency data products.\nLeverage AI-augmented development workflows (e.g., Claude Code) to accelerate pipeline development and documentation.\nRequirements\n7+ years of hands-on data engineering experience, with meaningful depth in streaming/event-driven systems, not just batch pipelines.\nProven experience designing and building near real-time pipelines from scratch (e.g., Kafka, Kinesis, Flink, Debezium/CDC) in a production environment.\nHands-on production experience with vector databases and embeddings (e.g., Zilliz, Pinecone, Weaviate, pgvector, Milvus) - ideally having built this infrastructure from the ground up rather than just consuming a managed AI feature.\nAdvanced proficiency in SQL and Python.\nWorking knowledge of a cloud warehouse/lakehouse platform (Snowflake, BigQuery, or Databricks) and dbt - you'll use these, but they're the storage/transform layer supporting the streaming and AI work, not the main focus.\nProven experience building or materially contributing to an end-to-end production data environment, ideally as an early or founding data hire.\nFamiliarity with B2B SaaS and recurring revenue data models (customer lifecycle, pipeline/conversion data).\nWorking knowledge of BI/reporting tools (e.g., Looker, Tableau, Power BI) as a downstream consumer of your data models.\nAbility to work independently and drive multi-stakeholder projects in a lean, scrappy, fast-moving environment - comfortable with ambiguity and building without a lot of existing infrastructure or process.\nSkills and Knowledge\nStrong command of event streaming and CDC tooling.\nHands-on experience with vector databases (Pinecone, Weaviate, pgvector, Milvus, or similar), including embedding strategies and chunking approaches for retrieval use cases.\nWorking knowledge of ELT/ETL tools (e.g., Fivetran, Airbyte) for batch use cases.\nWorking knowledge of data observability/reliability practices - automated alerting, lineage tracking.\nFluency with AI-augmented development tools (e.g., Claude, Copilot) to accelerate engineering and documentation.\nAccommodations:\nHarbor Compliance is committed to providing any reasonable accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.\nCompensation:\nHarbor Compliance’s base salary range for this role is listed below. Compensation at the time of offer is based on factors such as skill set, experience, qualifications, and work location. Salary is one part of Harbor Compliance’s total compensation package. Other benefits may include health benefits, flexible paid time off, parental leave, fertility and adoption assistance, 401(k), and educational reimbursement. Note that the salary range and benefits apply only to U.S.-based candidates.\nPay Transparency Policy Statement\nHarbor Compliance will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by Harbor Compliance, or (c) consistent with Harbor Compliance’s legal duty to furnish information.\nEqual Opportunity Statement\nHarbor Compliance is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.\nNotice Regarding the Use of Selection Technology\nHarbor Compliance uses third-party automated tools and skills assessments (such as Testlify and Rippling) to help evaluate job applications and streamline our hiring workflow. These tools assist our recruitment team in reviewing qualification trends and scheduling, but all final employment decisions are made solely by humans on our Talent Success team, and all tools are subject to human oversight.\nDepending on your location, local laws may grant you specific disclosure rights or the option to request an alternative evaluation process. If you require a reasonable accommodation or wish to opt out of automated assessment steps due to regional regulations, please notify your recruiter. 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