{"id":3517622,"url":"https://alion.io/job/campbell-global-associate-analytics-data-engineer","title":"Associate - Analytics Data Engineer","company":{"id":2649833,"name":"Campbell Global","domain":"campbellglobal.com","url":"https://alion.io/company/campbellglobal","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":94,"open_postings":149,"ghost_share":0.06,"stale_share":0.215,"repost_share":0.114,"time_to_fill_p50_days":13,"computed_at":"2026-11-04T06:34:25Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","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":21000,"max_usd":46000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Databricks","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Azure Data Factory","optional":true},{"name":"Dagster","optional":true},{"name":"Looker","optional":true},{"name":"Tableau","optional":true}],"status":"live","first_seen_at":"2026-10-26T13:05:33Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-11-04T19:23:09Z","board_verified":true,"closed_at":null,"days_open":9,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":9},"description":"Join a team focused on analytics enablement-designing analytics-ready data models and a trusted semantic layer that standardizes business metrics. You will partner with stakeholders to translate requirements into well-modeled datasets in Databricks and Snowflake, using SQL as your primary language and Python when needed. You will define consistent metrics and semantic conventions that enable scalable self-service reporting. You will help create a data ecosystem where consumers trust and reuse what has been built.\nJob summary\nAs an Analytics Solutions Associate within Analytics Engineering, you will build analytics-ready data models and a trusted semantic layer that standardizes business metrics. You will partner with stakeholders to translate requirements into governed, reusable datasets and semantic definitions. You will own the structure and usability of downstream analytics by defining grains, dimensions, facts, conformed entities, and metric logic so teams can move faster with confidence. You will collaborate with upstream engineering partners to ensure source-to-model alignment and ensure data quality and documentation meet a high bar. Success looks like consistent key performance indicator definitions across dashboards, clear semantic conventions, and performant, well-documented models.\nJob responsibilities\n Lead development of analytics data models (dimensional and/or domain-oriented) optimized for reporting, business intelligence, and self-service consumption.\n Design and maintain a semantic layer (standardized metrics, dimensions, entities, and business definitions) to ensure consistency across dashboards and analyses.\n Translate stakeholder requirements into clear modeling deliverables (entities, grains, metric definitions, acceptance criteria).\nBuild transformations primarily in SQL, leveraging Python when needed for complex logic, automation, or validation.\n Implement and champion data quality controls (tests, reconciliations, anomaly checks) tied to business-critical metrics.\n Optimize model performance in Snowflake and/or Databricks (efficient joins, partitioning and clustering strategies where applicable, cost/performance trade-offs).\n Collaborate with upstream teams on source system understanding (including semi-structured data and non-relational sources) and ensure analytics models reflect correct business meaning.\nEstablish modeling standards: naming conventions, documentation, lineage, metric governance, and change management for semantic definitions.\nSupport enablement by documenting curated datasets, creating user guidance, and helping consumers adopt the semantic layer correctly.\nRequired qualifications, capabilities, and skills\nMinimum education and experience required: Master’s degree in Information Technology, Computer Science, Management Information Systems, Operations Research or related field of study plus 3 years of experience in the job offered or as Analytics Engineer or related occupation. The employer will alternatively accept a Bachelor’s degree in Information Technology, Computer Science, Management Information Systems, Operations Research or related field of study plus 5 years of experience in the job offered or as Analytics Engineer or related occupation.\nAdvanced SQL skills (complex joins, performance tuning, incremental logic).\nStrong understanding of data modeling (facts and dimensions, grains, conformed dimensions, slowly changing dimensions, metric design).\nDemonstrated experience building or operating a semantic layer or metrics framework (tool-agnostic; ability to standardize key performance indicator logic and definitions).\nComfort working with semi-structured data (JSON) and non-relational sources and modeling them for analytics.\nExposure to data governance concepts (role-based access control, data classification, lineage, audit requirements).\nWorking experience with Snowflake and/or Databricks in an analytics context.\nPractical Python skills for data workflows (validation, automation, notebooks and scripts).\nAbility to partner with stakeholders, clarify ambiguous requirements, and drive to measurable outcomes.\nStrong documentation habits and attention to data correctness.\nPreferred qualifications, capabilities, and skills\nExperience with testing and documentation.\nFamiliarity with business intelligence tooling and semantic consumption patterns (for example, Tableau, Sigma, or Looker concepts).\nKnowledge of orchestration and observability (for example, Airflow, Dagster, or Azure Data Factory; logging and alerting; service level agreement mindset).","description_format":"text","description_chars":4577,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Forest Resources","Asset Management & Funds","Land & Agriculture Property"],"lifecycle":[{"event":"open","at":"2026-10-30T11:02:00Z"}],"visa":[],"liveness":{"score":78,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.87,"p_room":0.9,"age_days":8,"expected_fill_days":13,"reasons":["conf:2","velocity","win:mid","comp:brand"],"computed_at":"2026-11-04T06:34:25Z"},"pay":null,"html_url":"https://alion.io/job/campbell-global-associate-analytics-data-engineer","json_url":"https://alion.io/job/campbell-global-associate-analytics-data-engineer.json","meta":{"generated_at":"2026-11-04T21:24:42Z","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":33175,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-05T00:00:00Z"}},"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":2649833},"rest":"https://alion.io/mcp/rest/get_company?id=2649833"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fcampbell-global-associate-analytics-data-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%2Fcampbell-global-associate-analytics-data-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%2Fcampbell-global-associate-analytics-data-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/campbell-global-associate-analytics-data-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fcampbell-global-associate-analytics-data-engineer"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3517622}},{"tool":"search_jobs","arguments":{"company":"campbellglobal.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3517622},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); 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