{"id":19940,"url":"https://alion.io/job/clickup-staff-data-engineer","title":"Staff Data Engineer","company":{"id":5670,"name":"ClickUp","domain":"clickup.com","url":"https://alion.io/company/clickup","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":98,"open_postings":10,"ghost_share":0,"stale_share":0.1,"repost_share":0,"time_to_fill_p50_days":55,"computed_at":"2026-10-03T05:45:00Z"}},"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":"inferred","locations":[],"countries":[],"hiring_countries":["US","CA"],"hiring_countries_total":2,"salary":{"min":169000,"max":211000,"currency":"USD","period":"year","gross":null,"usd_annual":211000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Aurora","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"AWS Fargate","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"CI/CD","optional":false},{"name":"ClickUp","optional":false},{"name":"Dagster","optional":false},{"name":"dbt","optional":false},{"name":"Docker","optional":false},{"name":"DynamoDB","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Feature Store","optional":false},{"name":"Git","optional":false},{"name":"LLM","optional":false},{"name":"Prefect","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"FinOps","optional":true},{"name":"Machine Learning","optional":true}],"status":"live","first_seen_at":"2026-06-30T09:26:01Z","employer_posted_date":"2026-06-30","last_verified_at":"2026-10-03T23:28:21Z","board_verified":true,"closed_at":null,"days_open":95,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":95},"description":"At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible.\nWe're looking for a Staff Data Engineer to own the architecture and technical vision of our data platform. This is a high-leverage, high-autonomy role where you'll set the technical bar for the team, drive cross-functional alignment on data infrastructure strategy, and solve our hardest engineering problems. You'll operate across AWS serverless technologies, Snowflake, dbt, and Terraform, but your impact goes well beyond any single tool: you'll shape how we think about reliability, scalability, cost, and developer experience at the platform level.\nThis role is for someone who doesn't just build great systems, but makes the engineers around them better.\nThe Role:\nOwn the technical architecture of ClickUp's data platform, making design decisions that balance scalability, cost, reliability, and velocity.\n\nDefine and drive the technical roadmap for data infrastructure in partnership with leadership.\n\nDesign systems at scale: build frameworks, abstractions, and patterns that other engineers use daily.\n\nLead complex, cross-team technical initiatives spanning data engineering, analytics engineering, data science, and data analytics.\n\nDrive cost optimization across cloud infrastructure and compute, turning efficiency into a competitive advantage.\n\nBuild and evolve our data pipelines using AWS serverless (Lambda, Fargate, Step Functions, Kinesis, S3, DynamoDB, Aurora), Snowflake, and dbt.\n\nEstablish and champion engineering standards: observability, testing, CI/CD, code review, and documentation practices.\n\nDesign and maintain infrastructure for AI/ML workloads, including LLM frameworks, feature pipelines, training data systems, and model monitoring.\n\nMentor senior engineers, provide technical guidance through design reviews, and raise the overall engineering quality of the team.\n\nInfluence org-wide technical decisions and represent data engineering in company-level architecture discussions.\n\nQualifications:\nSignificant professional experience in data engineering or backend/infrastructure engineering, with at least 3 years operating at a senior or staff level.\n\nProven track record of owning architecture for data platforms or large-scale distributed systems.\n\nDeep expertise in AWS cloud services (Lambda, Fargate, Step Functions, S3, Kinesis, DynamoDB, Aurora) and infrastructure as code (Terraform and/or CDK).\n\nExpert-level SQL and Snowflake (or equivalent cloud data warehouse) knowledge, including performance tuning and cost optimization.\n\nStrong experience with dbt and modern ELT/ETL patterns at scale.\n\nAdvanced Python skills with emphasis on building reusable libraries, frameworks, and tooling.\n\nHands-on experience with orchestration frameworks (Airflow, Dagster, or Prefect) in production environments.\n\nExperience building data infrastructure for AI/ML: feature stores, training pipelines, embedding pipelines, model serving, or LLM integration.\n\nDeep understanding of streaming and event-driven architectures (Kinesis, Kafka, or equivalent).\n\nMastery of CI/CD, Git workflows, containerization (Docker), and deployment automation.\n\nStrong communication skills: ability to write technical RFCs, influence without authority, and translate complex trade-offs for non-technical stakeholders.\n\nTrack record of mentoring and growing engineers, with a multiplier mindset.\n\nDesirable\nExperience operating data platforms at high scale (petabyte-level warehouses, millions of events/sec).\n\nFamiliarity with data mesh or data product paradigms.\n\nExperience with FinOps practices and cloud cost management at scale.\n\nPrior experience in a technical leadership role without direct reports (staff/principal IC track).\n\nContributions to open-source data tools or technical communities.\n\nEqual Opportunity Employer\nClickUp is an Equal Opportunity Employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.\nPrivacy Notice\nClickUp collects and processes personal data in accordance with applicable data protection laws. You can find further details by viewing our Global Candidate Privacy Notice.\nIf you are a Philippine Job Applicant, please also see our Philippine Data Privacy Notice for further details.\nVisa Sponsorship\nPlease note we are unable to sponsor or take over sponsorship of an employment visa for roles outside of engineering and product at this time. Sponsorship for engineering and product roles is not guaranteed, but is instead based on the business needs for that specific role at that time. Please reach out to the recruiter with any questions.\nFraud Alert\nClickUp Talent Acquisition will only initiate contact via an @clickup.com email or through our official careers portal on clickup.com. We will never request fees, payments, or sensitive personal information. Please disregard any offers received outside these channels and report them to .\nAI Processing Notice\nClickUp may use artificial intelligence and machine learning technologies to help review and screen candidates' employment applications against role-related criteria. These tools support, but do not replace, human decision-making. If you have questions or need an accommodation in the recruitment process, please contact us at .","description_format":"text","description_chars":5670,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"},{"name":"Canada","iso":"CA","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Office & Productivity Software","AI Agents","AI Search"],"lifecycle":[{"event":"open","at":"2026-06-30T09:26:01Z"}],"visa":[],"liveness":{"score":33,"band":"fade","label":"Fading","p_open":1,"p_active":0.903,"p_room":0.36,"age_days":94,"expected_fill_days":55,"reasons":["conf:16","velocity","win:tail","crowd:"],"computed_at":"2026-10-03T05:45:00Z"},"pay":{"stated_usd_annual":211000,"is_top_pay":true},"html_url":"https://alion.io/job/clickup-staff-data-engineer","json_url":"https://alion.io/job/clickup-staff-data-engineer.json","meta":{"generated_at":"2026-10-04T00:21:30Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":309,"day_limit":5000,"remaining_today":4691,"minute_limit":60,"resets_at":"2026-10-05T00:00:00Z"}}}