{"id":24602,"url":"https://alion.io/job/juniper-square-senior-staff-software-engineer-data","title":"Senior Staff Software Engineer, Data","company":{"id":6722,"name":"Juniper Square","domain":"junipersquare.com","url":"https://alion.io/company/juniper-square","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":89,"open_postings":13,"ghost_share":0,"stale_share":0.385,"repost_share":0.077,"time_to_fill_p50_days":46,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Backend","role_family":"Backend","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":182000,"max_usd":388000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2198},"experience_years_min":15,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Data Vault","optional":false},{"name":"dbt","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Feature Store","optional":false},{"name":"Flink","optional":false},{"name":"GCP","optional":false},{"name":"Java","optional":false},{"name":"LLM","optional":false},{"name":"Looker","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false}],"status":"live","first_seen_at":"2026-07-08T22:56:21Z","employer_posted_date":"2026-07-08","last_verified_at":"2026-10-18T07:33:06Z","board_verified":true,"closed_at":null,"days_open":101,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":101},"description":"About Juniper Square\nPrivate markets are one of the largest, most complex, and most underserved corners of global finance. Our mission at Juniper Square is to unlock their full potential. We’re the Operations Partner trusted by 2,300+ GPs, unifying technology, data, and fund administration services into a single platform that helps GPs move faster, make better decisions, and scale with precision. With $300B+ under administration and 700,000+ LPs on platform, we’ve built the scale to match our ambition. And with JunieAI, our purpose-built AI platform, we’re reimagining how private markets operate, embedding intelligence across every workflow. Founder-led since 2014, backed by $350M+ in funding, and now 1,000+ employees strong, we’re building a company designed to shape the future of private markets for decades to come.\nOur culture is built for people who want to do ambitious, meaningful work alongside exceptionally talented teammates. We think like owners, move with urgency, and take pride in solving hard problems that truly matter to our customers and the future of private markets. We believe the best ideas come from open debate, deep collaboration, and diverse perspectives, which is why we believe transparency is the default and feedback makes us stronger. If you’re energized by high standards, rapid growth, and the opportunity to help define a category at a pivotal moment, come join us!\nJuniper Square offers employees a variety of ways to work, ranging from a fully remote experience to working full-time in one of our physical offices. We invest heavily in digital-first operations, allowing our teams to collaborate effectively across 27 U.S. states, 2 Canadian Provinces, India, Luxembourg, and England. We also have physical offices in San Francisco, New York City, Mumbai and Bangalore for employees who prefer to work in an office some or all of the time.\nAbout your role\nWe are seeking a Senior Staff Software Engineer to lead the transformation of our current data engineering and analytics function into a modern, scalable, product-oriented Data Platform organization. You will define the vision, architecture, operating model, and execution roadmap required to evolve from project-based data delivery to a platform that enables self-service, reliable, governed, and analytics-ready data across the company.\nThis is a deeply hands-on leadership role for a technical expert who actively designs systems, prototypes solutions, reviews code, and guides teams through complex challenges. You will modernize our data stack, establish platform standards, introduce best practices for reliability and governance, and enable teams across the business to build data products efficiently and safely.\nIn addition to platform transformation, you will ensure the data ecosystem delivers high-quality analytics and actionable insights. You will define architecture across ingestion, processing, modeling, semantic layers, analytics, and AI/ML enablement, ensuring data is trustworthy, accessible, secure, and performant.\nYou will work closely with engineering leadership, product teams, analytics, and executive stakeholders to align technology strategy with business outcomes, mentor engineers, and build a data-driven culture. Success in this role means not only delivering a modern platform but also elevating the team’s capabilities, processes, and ways of working to operate as a true Data Platform organization.\nWhat you’ll do\nArchitecture & Technical Leadership\nDefine and own the end-to-end data and analytics architecture strategy\n\nDesign scalable batch, streaming, and real-time data systems\n\nEstablish standards for data modeling, semantic layers, and reporting\n\nLead architecture reviews and technical decision-making\n\nDrive adoption of modern architectures (lakehouse, data mesh, real-time analytics)\n\nHands-On Engineering\nDesign and prototype critical data platform components\n\nWrite production-quality code for complex or high-impact areas\n\nReview schemas, transformations, dashboards, and analytics models\n\nTroubleshoot performance and reliability issues across pipelines and queries\n\nOptimize workloads for latency, concurrency, and cost\n\nData Platform & Pipeline Ownership\nDesign and architect a scalable data platform supporting ingestion, transformation, and delivery of both structured and unstructured data across batch and real-time pipelines.\n\nDesign a \"Data for Agents\" strategy, ensuring our data warehouse is structured with the semantic layers and metadata necessary for LLMs to navigate it accurately.\n\nBuild AI-ready data infrastructure, including vector stores, embedding pipelines, and retrieval systems that power LLM and agentic workflows.\n\nDevelop a RAG-ready data architecture that enables trusted enterprise data retrieval with strong lineage, governance, security, and observability.\n\nCreate curated data products and reusable APIs that make high-quality datasets easily consumable by applications, analytics platforms, and AI agents.\n\nEnable self-service data access for engineering, analytics, and business teams through standardized models, semantic layers, and platform capabilities.\n\nPartner with AI, product, and engineering teams to support training datasets, feature stores, and production AI inference pipelines.\n\nBuild agentic ETL/ELT pipelines that use AI agents to autonomously discover sources and generate transformations.\n\nEnsure reliability, scalability, and resilience of the platform, including high availability, monitoring, and disaster recovery readiness.\n\nAnalytics & Business Intelligence\nPartner with product, finance, business operations, and leadership teams to define analytics needs\n\nDesign scalable data models for reporting and advanced analytics\n\nEnsure analytics solutions are performant, trustworthy, and easy to use\n\nDrive adoption of data-driven culture through reliable insights\n\nGovernance, Quality & Security\nDefine data governance, lineage, cataloging, and metadata standards\n\nEstablish data quality frameworks and validation processes\n\nEnsure privacy, compliance, and secure access to sensitive data\n\nImplement role-based access controls and auditability\n\nLeadership & Collaboration\nMentor senior engineers, analytics engineers, and data scientists\n\nPartner with product, ML, platform, and business teams\n\nTranslate business questions into scalable data solutions\n\nInfluence roadmaps using data platform and analytics considerations\n\nAct as the executive technical authority for data and analytics\n\nOperational Excellence\nDefine SLAs/SLOs for data availability, freshness, and accuracy\n\nEstablish monitoring, alerting, and incident response processes\n\nOptimize cloud costs and query performance\n\nSupport capacity planning for data growth\n\nCulture & Enablement\nBe an evangelist for pragmatic AI adoption.\n\nHelp establish a culture of outcome-driven innovation.\n\nQualifications\nRequired\nAdvanced degree in Computer Science, Engineering, or related field\n\n15+ years in data engineering, analytics engineering, or data platform roles\n\nProven experience architecting large-scale data and analytics systems\n\nStrong hands-on experience with modern data stacks in cloud environments\n\nDeep expertise in data modeling for analytics (dimensional, star/snowflake, Data Vault, etc.)\n\nAdvanced SQL skills and proficiency in Python, Scala, or Java\n\nAdvanced expertise in dimensional data modeling and semantic layers (e.g., dbt, Cube) to provide \"agent-readable\" context.\n\nExpertise in real-time streaming frameworks such as Spark, Flink, or Beam.\n\nExperience building reporting and BI solutions at scale\n\nStrong understanding of both batch and real-time architectures\n\nHands-on experience with AWS, Azure, or GCP data services\n\nExperience with BI tools (e.g., Looker, Tableau, Power BI, etc.)\n\nStrong understanding of data governance and security best practices\n\nAbility to operate at both executive and deeply technical levels\n\nNice to Have\nExperience supporting AI/ML pipelines and feature engineering\n\nFamiliarity with real-time analytics and event-driven architectures\n\nExperience implementing semantic layers or metrics stores\n\nBackground in high-growth SaaS or data-intensive organizations\n\nExperience with experimentation platforms or product analytics\n\nCompensation\nCompensation for this position includes a base salary, equity and a variety of benefits. The U.S. base salary range for this role is $235,000 - $285,000 USD. Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable.\nBenefits include:\nHealth, dental, and vision care for you and your family\n\nLife insurance\n\nMental wellness coverage\n\nFertility and growing family support\n\nFlex Time Off in addition to company paid holidays\n\nPaid family leave, medical leave, and bereavement leave policies\n\nRetirement saving plans\n\nAllowance to customize your work and technology setup at home\n\nAnnual professional development stipend\n\nYour recruiter can provide additional details about compensation and benefits.\n#LI-TG1","description_format":"text","description_chars":9067,"description_truncated":false,"requirements":{"experience_years_min":15,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity","Life 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