{"id":3090613,"url":"https://alion.io/job/notion-director-analytics","title":"Director Analytics","company":{"id":14288,"name":"Notion","domain":"notion.com","url":"https://alion.io/company/notion","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":83,"open_postings":10,"ghost_share":0,"stale_share":0.5,"repost_share":0,"time_to_fill_p50_days":78,"computed_at":"2026-10-25T05:49:26Z"}},"role":"Analytics","role_family":"Analytics","seniority":"head","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":39000,"max_usd":85000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":351},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Google BigQuery","optional":false},{"name":"LLM","optional":false},{"name":"Looker","optional":false},{"name":"Machine Learning","optional":false},{"name":"Power BI","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false}],"status":"live","first_seen_at":"2026-10-22T14:35:30Z","employer_posted_date":null,"last_verified_at":"2026-10-22T14:35:30Z","board_verified":false,"closed_at":null,"days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"Responsibilities: \nLead the next generation of our Data Mart: Redesign and optimise data models to support large-scale analytics and faster decision-making.\nDefine the tools and frameworks for data creation, transformation, and consumption across the company.\nBuild unified data views: Integrate behavioural and transactional data into structured, query-optimised flat tables that support diverse analytics use cases.\nOwn analytics across mobile, web, marketing, product, and operations data streams, ensuring consistent data definitions and scalability.\nPartner with business, product, marketing, CRM, operations and finance teams to ensure data is democratised and actionable.\nEstablish data governance, quality standards, and best practices for the org.\nDrive adoption of self-service analytics and empower teams with the right dashboards, reporting, and insights.\n\nIntroduce and scale AI/ML-driven insights: \nCollaborate with product and engineering to enable LLM-powered use cases (e. g., conversational analytics, decision copilots), as well as ML-driven use cases such as personalisation, predictive modelling, and anomaly detection.\nAdditionally, build and mentor a cross-functional analytics team spanning business/operations analytics, marketing/CRM analytics, and product/finance analytics.\nPartner with engineering leadership to ensure scalability, reliability, and efficiency of the data infrastructure.\n\nRequirements: \n8+years in data analytics leadership, with proven success in building data marts and defining enterprise-wide data consumption strategies.\nStrong track record of running analytics across mobile, web, marketing, product, and operations data ecosystems.\nDeep technical expertise in data modelling, flat table structures, and query optimisation for large-scale systems.\nHands-on experience with both behavioural and transactional data, and integrating them into a single analytics layer.\nStrong knowledge of modern data stack (SQL, ETL/ELT, cloud data warehouses like Snowflake/BigQuery/Redshift, BI tools like Looker/PowerBI/Tableau).\nAI Expertise: Experience working with or enabling AI/ML and LLM-based use cases, including building data pipelines for AI applications, supporting use cases such as process automation and conversational analytics, and partnering with engineering to productionise AI-driven solutions.\nML Competency: Familiarity with machine learning workflows (data pipelines for ML, feature engineering, model monitoring) and ability to guide data scientists in building predictive/ML models.\nProven ability to build and scale analytics teams, with experience in functions such as business/operations, marketing/CRM, and product/finance analytics.\nStrong business acumen and ability to translate data into actionable insights for growth, retention, and efficiency.\nExcellent stakeholder management and communication skills, comfortable influencing at the CXO level.\nSkills\nBigQuery, ELT, ETL, Redshift, SQL, Snowflake, analytics","description_format":"text","description_chars":2978,"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":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Office & Productivity Software","Project & Work Management Software","Intranet & Knowledge 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