{"id":836725,"url":"https://alion.io/job/castletontowerllc-director-senior-director-ai-data-engineering","title":"Director / Senior Director, AI & Data Engineering","company":{"id":690872,"name":"Castleton Tower Consulting, LLC","domain":"castletontowerllc.com","url":"https://alion.io/company/castletontowerllc","size_band":"51-200","is_staffing_agency":false,"is_intermediary":false,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":5,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-09-23T05:45:00Z"}},"role":"Leadership","role_family":"Leadership","seniority":"head","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":180000,"max_usd":336000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1323},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Claude Code","optional":false},{"name":"Copilot","optional":false},{"name":"Cursor","optional":false},{"name":"Dagster","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Looker","optional":false},{"name":"OpenAI Codex","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false}],"status":"live","first_seen_at":"2026-05-12T17:12:26Z","employer_posted_date":"2026-05-12","last_verified_at":"2026-09-23T10:45:47Z","board_verified":true,"closed_at":null,"days_open":134,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":133},"description":"The Firm\nCastleton Tower is a boutique consulting firm founded by executives who have built and led quantitative research, data science, and technology teams at top-tier hedge funds and asset managers. We work exclusively with investment management firms, including asset allocators, asset managers, hedge funds, family offices, and RIAs, helping them modernize data infrastructure and build AI-ready foundations.\nOur engagements combine senior strategy with hands-on implementation. We assess technical and business strategy, design the architecture, and build the data and AI infrastructure needed to support better investment decisions.\nThe Opportunity\nWe are looking for a senior data and AI leader to design, build, and ultimately manage a modern data engineering function for a prominent asset allocator client. This is a leadership role for someone who can operate from first principles: define the platform strategy, build production systems, hire and develop talent, and work directly with senior investment and operating stakeholders.\nThis is not a narrow individual-contributor engineering role. The right person can still get close to the code, but their broader mandate is to turn fragmented data, tooling, and process into a scalable operating model for an investment organization.\nWhat You Will Own\nData team design: Define the target operating model, roles, roadmap, standards, and ways of working for a high-performing data engineering and analytics team.\n\nPlatform architecture: Design the data warehouse/lakehouse, semantic layers, orchestration, governance, quality controls, and analytics delivery patterns.\n\nHands-on delivery: Build and review production-grade Python, SQL, dbt, orchestration, and cloud infrastructure work where needed.\n\nAI-enabled engineering: Use modern AI development tooling, including tools such as Claude Code, OpenAI Codex, Cursor, GitHub Copilot, and Databricks AI capabilities, to accelerate delivery without compromising quality, controls, or maintainability.\n\nStakeholder partnership: Translate needs from CIOs, PMs, COOs, operations teams, and finance stakeholders into durable data products and operating processes.\n\nPeople leadership: Hire, coach, and manage engineers and analytics talent; establish review practices, delivery rituals, technical standards, and performance expectations.\n\nCore Responsibilities\nLeadership and Operating Model\nDesign and implement the data team structure, hiring plan, delivery model, and long-term technical roadmap.\n\nSet engineering standards for code review, testing, documentation, observability, data quality, and production support.\n\nManage internal team members, contractors, vendors, and implementation partners where appropriate.\n\nBuild a culture of ownership, technical rigor, and pragmatic delivery.\n\nData Platform and Analytics Delivery\nArchitect and build scalable data platforms across warehouse, lakehouse, orchestration, transformation, and BI layers.\n\nDevelop data models and applications that support portfolio analytics, investment operations, risk reporting, finance, and executive reporting.\n\nCreate durable pipelines and controls for high-value investment and operational datasets.\n\nEvaluate and rationalize tooling across Snowflake, Databricks, dbt, Dagster/Airflow, cloud infrastructure, BI, and internal applications.\n\nAI and Modern Engineering Workflows\nUse AI coding assistants and agentic workflows to accelerate software and data delivery while maintaining security, review, and testing discipline.\n\nIdentify high-leverage AI use cases across data ingestion, documentation, analytics, workflow automation, and research operations.\n\nDesign human-in-the-loop processes for AI-generated code, analysis, and operational outputs.\n\nHelp the organization build the data and governance foundation required for responsible AI adoption.\n\nQualifications\nRequired\n10+ years of progressive experience in data engineering, analytics engineering, data platforms, or technical data leadership.\n\n3+ years managing engineers, analytics engineers, data platform teams, or cross-functional technical delivery teams.\n\nProven ability to design and build production data platforms using Python, SQL, modern warehouse/lakehouse technologies, and orchestration tools.\n\nStrong architectural judgment across data modeling, governance, quality, observability, security, and operational resilience.\n\nPractical fluency with AI-assisted development tools such as Claude Code, OpenAI Codex, Cursor, GitHub Copilot, or similar systems.\n\nAbility to communicate clearly with senior non-technical stakeholders and translate business needs into durable technical systems.\n\nExecutive presence, high ownership, and comfort operating in ambiguous environments.\n\nStrongly Valued\nExperience in investment management, asset allocation, hedge funds, private markets, family offices, RIAs, fintech, or financial data products.\n\nExperience building or modernizing data teams in a high-expectation investment, finance, or institutional environment.\n\nHands-on exposure to Snowflake, Databricks, dbt, Dagster, Airflow, AWS, Azure, Sigma, Tableau, Looker, or similar tooling.\n\nExperience with portfolio analytics, manager research, risk reporting, investment operations, fund accounting, or performance reporting datasets.\n\nExperience evaluating vendors and implementation partners, including build-versus-buy decisions.\n\nPersonal Attributes\nBuilder-manager mindset: able to set direction, manage people, and still understand the technical details.\n\nPragmatic systems thinker who can connect architecture, process, talent, and business outcomes.\n\nHigh standards for data quality, reliability, documentation, and maintainability.\n\nComfortable challenging assumptions while staying collaborative with senior stakeholders.\n\nMotivated by the opportunity to build a durable data function inside a sophisticated investment organization.\n\nLocation and Placement\nLocation: Hybrid, Northeast U.S.\nThis role is intended for placement at a prominent asset allocator client. The successful candidate should be comfortable working closely with senior investment, operations, and technology leaders and spending regular time in person as needed.\nCompensation: Competitive total compensation commensurate with experience.","description_format":"text","description_chars":6271,"description_truncated":false,"requirements":{"experience_years_min":10,"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"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Data & Analytics","Financial Services","Data Integration"],"lifecycle":[{"event":"open","at":"2026-09-12T19:26:31Z"}],"liveness":{"score":11,"band":"cold","label":"Long shot","p_open":1,"p_active":0.399,"p_room":0.28,"age_days":133,"expected_fill_days":41,"reasons":["conf:9","win:tail","crowd:"],"computed_at":"2026-09-23T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/castletontowerllc-director-senior-director-ai-data-engineering","json_url":"https://alion.io/job/castletontowerllc-director-senior-director-ai-data-engineering.json","meta":{"generated_at":"2026-09-23T18:58:06Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers"}}