{"id":1606511,"url":"https://alion.io/job/innodata-lead-analytics-engineer","title":"Lead Analytics Engineer","company":{"id":48089,"name":"Innodata","domain":"innodata.com","url":"https://alion.io/company/innodata","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":95,"open_postings":8,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":2625,"computed_at":"2026-10-09T06:01:00Z"}},"role":"Analytics","role_family":"Analytics","seniority":"lead","employment_type":"contractor","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":130000,"max":150000,"currency":"USD","period":"year","gross":null,"usd_annual":150000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Airflow","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"BigQuery","optional":false},{"name":"Dagster","optional":false},{"name":"dbt","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Looker","optional":false},{"name":"Power BI","optional":false},{"name":"Prefect","optional":false},{"name":"Presto","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Superset","optional":false},{"name":"Tableau","optional":false},{"name":"Trino","optional":false}],"status":"live","first_seen_at":"2026-08-19T22:13:48Z","employer_posted_date":"2026-08-27","last_verified_at":"2026-10-10T01:20:47Z","board_verified":true,"closed_at":null,"days_open":51,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":51},"description":"Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers.\nScope of the Role: \nWe are hiring a Staff / Lead-level Data Analyst / Analytics Engineer to embed with the Monetization Data Science & Analytics team as a senior individual contributor and technical leader. This person will be the go-to analytics expert for advertiser revenue, monetization performance, and growth metrics - trusted by Data Scientists, Analysts, PMs, and Engineering leaders to drive high-impact work end-to-end.\nThis is a staff-level Individual Contributor role, not a mid-level execution seat. The successful candidate operates as:\nA trusted thought partner to Data Scientists and Product leaders - someone who improves the quality of the question before answering it.\nA technical leader who sets standards for data models, pipelines, and dashboards that others follow.\nA force multiplier who unblocks the team by identifying and fixing root causes across the data stack, not just building what's asked.\nWhat You’ll Own:\n50% - Analytics, Business Insights & Technical Leadership Partnering with Data Scientists and Product on the hardest analytics problems; driving metric definitions; reviewing others' analyses; setting standards for the team's analytics work.\n30% - Data Engineering & Pipeline Ownership Architecting and owning production SQL pipelines, data models, and data cubes; designing and operating Airflow DAGs; setting the bar for data quality, reliability, and reconciliation across the domain.\n 20% - Data Visualization, Metric Governance & Enablement Owning executive-visibility dashboards in Tableau / Superset; defining and governing metrics; enabling self-serve analytics for the broader Monetization org.\nAnalytics Leadership & Business Partnership\nServe as the senior analytics IC for the Monetization Analytics pod - the person Data Scientists and PMs come to with the hardest, most ambiguous data problems.\nImprove the quality of the question before answering - reframe vague asks into sharper, more valuable analytical approaches.\nLead end-to-end analytics initiatives that span data modeling, pipeline work, and dashboard delivery - with minimal supervision and clear stakeholder communication throughout.\nSet metric definitions and standards for advertiser revenue, monetization performance, funnel/cohort metrics, and experiment readouts - and drive consistency across dashboards.\nIndependently drive root-cause analysis on data discrepancies across dashboards, warehouses, or pipelines - including cross-team debugging when needed.\nReview, coach, and raise the bar on the work of other analysts and analytics engineers on the team.\nData Engineering & Pipeline Architecture\nArchitect and own production-grade SQL data pipelines (Presto / Trino / Hive / Spark SQL) - including making the right tradeoffs on incremental vs. full refresh, pre-aggregation, and cost/performance.\nDesign and own data cubes, aggregate tables, and semantic layers used by the whole Monetization Analytics function.\nAuthor, own, and operate Airflow DAGs for critical revenue and monetization pipelines - including SLAs, on-call posture, backfills, and incident response.\nSet and enforce standards for data quality, reconciliation, and observability - row counts, revenue tie-outs, distribution checks, anomaly alerting - across the domain.\nOptimize existing pipelines aggressively for cost and latency (partitioning, incremental refresh, query tuning on billion+ row tables) - and quantify the wins.\nContribute to cross-team technical decisions - table designs, upstream schema changes, migration plans (e.g., Hive → Trino) - via design docs and reviews.\nData Visualization, Metric Governance & Enablement\nOwn the design and quality of executive and cross-functional dashboards in Tableau and/or Superset.\nDrive metric governance - clear definitions, owners, source-of-truth queries, validation, deprecation.\nEnable self-serve analytics for Data Scientists, Analysts, and PMs - clear naming, documentation, certified metrics, sensible defaults, and coaching.\nYou’ll Thrive in This Role If You Have:\n9+ years of combined experience in Data Analytics, Business Intelligence, or Analytics Engineering roles.\nAt least 3+ years at Senior level or above in an analytics-adjacent role at a high-scale tech, ads-tech, marketplace, or fintech company.\nPrior experience as the most senior analytics IC on an embedded team - or a strong case for why they're ready to step into that role now.\nTrack record of leading end-to-end analytics initiatives - from ambiguous business question through data model, pipeline, dashboard, and rollout.\nPrior experience partnering directly with US-based Data Science, Product, and Engineering leaders as a full contributor.\nTechnical Skills - SQL & Data Engineering (Advanced)\nExpert-level SQL - deep proficiency with window functions, CTEs, complex joins, query optimization, incremental patterns, skew mitigation, and cost tuning on billion+ row tables.\nDeep hands-on with at least two of: Presto, Trino, Hive, Spark SQL, Snowflake, BigQuery, Redshift. Can reason about query plans and physical layout, not just syntax.\nAdvanced Airflow - has architected and operated large DAG ecosystems (50+ production DAGs), including cross-DAG dependencies, backfills at scale, and SLA management. Equivalent orchestrators (Dagster, Prefect) also acceptable if depth is comparable.\nData architecture & modeling depth - Kimball, star schema, dimensional modeling, OLAP cubes, wide fact tables, slowly-changing dimensions, semantic layer design. Can defend design tradeoffs in a design review.\nETL / ELT architecture - incremental loads, backfills, idempotency, data quality frameworks, lineage.\nPython for data work - pandas, PySpark, scripting, and light tooling development.\ndbt or equivalent transformation framework experience strongly preferred.\nExperience contributing to or reviewing design docs and RFCs for data platforms and pipelines.\nTechnical Skills - Visualization\nDeep, hands-on production experience building executive-grade dashboards in Tableau and/or Apache Superset (Looker, Power BI, Mode also acceptable).\nStrong opinions on dashboard design - headline vs. drilldown metrics, layout, filters, performance, self-serve UX.\nExperience driving metric governance and self-serve BI at an org level.\nAnalytics & Business Skills\nStrong grasp of KPI definition, metric design, funnel analysis, cohort analysis, and A/B testing methodology.\nDeep exposure to digital advertising / monetization metrics - impressions, clicks, CTR, CPM, CPC, CVR, ROAS, revenue attribution, incrementality - is strongly preferred.\nPrior experience at ads-tech, digital media, or major consumer/marketplace tech companies (Meta, Google, Amazon, Uber, DoorDash, Snap, TikTok, LinkedIn, Airbnb, Instacart, Pinterest peers, etc.) is a strong plus.\nComfort reading experiment results and challenging methodology when needed.\nLeadership, Communication & Ways of Working\nNative or near-native English (spoken and written) - this is a hard requirement.\nTrack record of leading initiatives end-to-end with minimal direction - scoping, aligning stakeholders, executing, and communicating results.\nComfortable pushing back on unclear or misdirected requirements and proposing better approaches.\nProlific writer of design docs, RFCs, requirement docs, and postmortems.\nExperience mentoring or coaching less-senior analysts and analytics engineers - even if not a formal manager.\nExecutive presence - can present analytics work to Director/VP-level stakeholders and defend recommendations.\nOperates with the ownership mindset of a permanent employee, even in a contract role.\nThe expected salary range for this position is $130,000 - $150,000 USD per year, based on experience, skills, and qualifications.\nPlease be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. \nIf you believe you’ve been targeted by a recruitment scam, please report it to Innodata at  and consider reporting it to the FTC at ReportFraud.ftc.gov.","description_format":"text","description_chars":8873,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"Proficiency (C2)","optional":false}]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Data Entry & Processing","AI Training Data & Annotation"],"lifecycle":[{"event":"open","at":"2026-10-01T19:52:38Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 2","filings_12m":2,"filings_prev_12m":2,"green_card_filings_12m":0,"median_offered_wage_usd":150000,"route":null,"cap_exempt":false,"checked_at":"2026-10-03T21:08:04+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)"],"filings_for_role_12m":1}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":50,"expected_fill_days":2625,"reasons":["conf:3","velocity","win:early"],"computed_at":"2026-10-09T06:01:00Z"},"pay":{"stated_usd_annual":150000,"is_top_pay":true},"html_url":"https://alion.io/job/innodata-lead-analytics-engineer","json_url":"https://alion.io/job/innodata-lead-analytics-engineer.json","meta":{"generated_at":"2026-10-10T02:13:10Z","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","counted_by":"address","units_charged":1,"used_today":3981,"day_limit":5000,"remaining_today":1019,"minute_limit":60,"resets_at":"2026-10-11T00:00:00Z"}},"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":48089},"rest":"https://alion.io/mcp/rest/get_company?id=48089"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Finnodata-lead-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%2Finnodata-lead-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%2Finnodata-lead-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/innodata-lead-analytics-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Finnodata-lead-analytics-engineer"}]}