{"id":1937841,"url":"https://alion.io/job/mercury-senior-analytics-engineer","title":"Senior Analytics Engineer","company":{"id":4381,"name":"Mercury","domain":"mercury.com","url":"https://alion.io/company/mercury","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":90,"open_postings":5,"ghost_share":0,"stale_share":0.4,"repost_share":0,"time_to_fill_p50_days":52,"computed_at":"2026-10-10T05:45:15Z"}},"role":"Analytics","role_family":"Analytics","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":["US","CA"],"hiring_countries_total":2,"salary":{"min":166600,"max":208300,"currency":"USD","period":"year","gross":null,"usd_annual":208300},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"dbt","optional":false},{"name":"Fivetran","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-05T22:29:31Z","employer_posted_date":"2026-10-05","last_verified_at":"2026-10-11T23:46:23Z","board_verified":true,"closed_at":null,"days_open":6,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":6},"description":"In 1989, Tim Berners-Lee wrote a proposal for CERN. CERN lost knowledge when people left, because its information was in many systems that did not connect. His solution was simple: link documents so that all people can find them and use them. That proposal became the World Wide Web.\nMercury has a similar challenge with data. Teams, models, and AI agents need data that they can find, understand, and trust. We are building an AI-native data platform that enables Mercury to have reliable analytics, accelerate product development, and enable the next generation of AI-powered products and internal tools.\nWe are hiring a Senior Analytics Engineer to help us accelerate. You’ll join a team of high-performing Data and Analytics Engineers building the shared foundations that power decisioning, automation, and measurement across the company, collaborating closely with Data Scientists and partners in Product, Engineering, and Operations. Your curiosity and bias toward action will drive meaningful impact as you build durable data products, unlock faster experimentation, and help teams ship propensity models, agentic workflows, and amazing data-driven experiences for our customers. Come grow with us.\nResponsibilities:\nDesign and build scalable data pipelines and business-conformed dimensional data marts in collaboration with Data Science, Engineering, Product, and Operations departments \nSupport the development and adoption of agentic tooling. We have our own AI Data Analyst (Hermes) and dbt Agent (Ralph) that are built and managed by our Analytics Engineers\nSupport self-service analytics workflows, Analytics Engineering skills, and dimensional data principles through implementation, education, and peer support\nHelp us implement the data and analytics products we’ll need to effect our bank charter\nContribute to the evolution of our data quality, governance, and security strategies\nContribute to our definition of Analytics Engineering standards and best practices\nYou may be a good fit if you:\nHave 4+ years of Analytics or Data Engineering experience\nHave expertise working in a full modern data stack including Fivetran / Airflow / Snowflake / dbt / Omni / Hex or equivalents\nAre proficient with SQL and have working experience with Python\nProficient using AI agents to accelerate your and your teammates’ work\nHave experience with dimensional data modeling principles and building data for scale\nTreat data products as a platform by prioritizing reusable, scalable deliverables\nDeliver readable code, strong tests, and quality documentation\nExperiment responsibly and share what you learn so everyone benefits\nPractice relentless empathy by meeting your stakeholders in Data, Product, Engineering, and beyond where they’re at and helping them succeed\nDiscern what’s needed from what’s wanted to deliver maximum impact\nStrong candidates may additionally have:\nBanking* or financial services industry experience\nExperience with agentic development and/or analytics workflows\nExposure to data governance, compliance, and security best practice\nA full-stack mindset and willingness to solve problems end-to-end by flexing into Data Engineering and Data Analysis\nIf this role interests you, we invite you to explore our public demo at demo.mercury.com. \n*Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.\nMercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.\nTotal Rewards\nThe total rewards package at Mercury includes base salary, equity (stock options/RSUs), and benefits.\nOur salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.\nOur target new hire base salary ranges for this role are the following :\nUS employees (any location):\n$166,600—$208,300 USD\nCanadian employees (any location):\n$157,400—$196,800 CAD","description_format":"text","description_chars":4668,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity","Stock options"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"},{"name":"Canada","iso":"CA","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Financial Services","Digital Banks & Neobanks"],"lifecycle":[{"event":"open","at":"2026-10-06T00:26:34Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":4,"expected_fill_days":52,"reasons":["conf:2","velocity","win:early"],"computed_at":"2026-10-10T05:45:15Z"},"pay":{"stated_usd_annual":208300,"is_top_pay":true},"html_url":"https://alion.io/job/mercury-senior-analytics-engineer","json_url":"https://alion.io/job/mercury-senior-analytics-engineer.json","meta":{"generated_at":"2026-10-12T01:54:09Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":2636,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-13T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":4381},"rest":"https://alion.io/mcp/rest/get_company?id=4381"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fmercury-senior-analytics-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fmercury-senior-analytics-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fmercury-senior-analytics-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/mercury-senior-analytics-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fmercury-senior-analytics-engineer"}]}