[Remote] Data Analytics

Note: The job is a remote job and is open to candidates in USA. Dice is hiring a Staff / Lead-level Data Analyst / Analytics Engineer to embed with the Monetization Data Science & Analytics team. The role serves as a senior individual contributor and technical leader, driving analytics initiatives, data modeling, production pipelines, dashboards, metric governance, and self-serve analytics for advertiser revenue and monetization performance.

Responsibilities

• Serve 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
• Improve the quality of the question before answering — reframe vague asks into sharper, more valuable analytical approaches
• Lead end-to-end analytics initiatives that span data modeling, pipeline work, and dashboard delivery — with minimal supervision and clear stakeholder communication throughout
• Set metric definitions and standards for advertiser revenue, monetization performance, funnel/cohort metrics, and experiment readouts — and drive consistency across dashboards
• Independently drive root-cause analysis on data discrepancies across dashboards, warehouses, or pipelines — including cross-team debugging when needed
• Review, coach, and raise the bar on the work of other analysts and analytics engineers on the team
• Architect 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
• Design and own data cubes, aggregate tables, and semantic layers used by the whole Monetization Analytics function
• Author, own, and operate Airflow DAGs for critical revenue and monetization pipelines — including SLAs, on-call posture, backfills, and incident response
• Set and enforce standards for data quality, reconciliation, and observability — row counts, revenue tie-outs, distribution checks, anomaly alerting — across the domain
• Optimize existing pipelines aggressively for cost and latency (partitioning, incremental refresh, query tuning on billion+ row tables) — and quantify the wins
• Contribute to cross-team technical decisions — table designs, upstream schema changes, migration plans (e.g., Hive → Trino) — via design docs and reviews
• Own the design and quality of executive and cross-functional dashboards in Tableau and/or Superset
• Drive metric governance — clear definitions, owners, source-of-truth queries, validation, deprecation
• Enable self-serve analytics for Data Scientists, Analysts, and PMs — clear naming, documentation, certified metrics, sensible defaults, and coaching

Skills

• ·         9+ years of combined experience in Data Analytics, Business Intelligence, or Analytics Engineering roles
• ·         At least 3+ years at Senior level or above in an analytics-adjacent role at a high-scale tech, ads-tech, marketplace, or fintech company
• ·         Prior 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
• ·         Track record of leading end-to-end analytics initiatives — from ambiguous business question through data model, pipeline, dashboard, and rollout
• ·         Prior experience partnering directly with US-based Data Science, Product, and Engineering leaders as a full contributor
• ·         Expert-level SQL — deep proficiency with window functions, CTEs, complex joins, query optimization, incremental patterns, skew mitigation, and cost tuning on billion+ row tables
• ·         Deep 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
• ·         Advanced 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
• ·         Data 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
• ·         ETL / ELT architecture — incremental loads, backfills, idempotency, data quality frameworks, lineage
• ·         Python for data work — pandas, PySpark, scripting, and light tooling development
• ·         Experience contributing to or reviewing design docs and RFCs for data platforms and pipelines
• ·         Deep, hands-on production experience building executive-grade dashboards in Tableau and/or Apache Superset (Looker, Power BI, Mode also acceptable)
• ·         Strong opinions on dashboard design — headline vs. drilldown metrics, layout, filters, performance, self-serve UX
• ·         Experience driving metric governance and self-serve BI at an org level
• ·         Strong grasp of KPI definition, metric design, funnel analysis, cohort analysis, and A/B testing methodology
• ·         Comfort reading experiment results and challenging methodology when needed
• ·         Native or near-native English (spoken and written) — this is a hard requirement
• ·         Track record of leading initiatives end-to-end with minimal direction — scoping, aligning stakeholders, executing, and communicating results
• ·         Comfortable pushing back on unclear or misdirected requirements and proposing better approaches
• ·         Prolific writer of design docs, RFCs, requirement docs, and postmortems
• ·         Experience mentoring or coaching less-senior analysts and analytics engineers — even if not a formal manager
• ·         Executive presence — can present analytics work to Director/VP-level stakeholders and defend recommendations
• ·         Operates with the ownership mindset of a permanent employee, even in a contract role
• ·         dbt or equivalent transformation framework experience strongly preferred
• ·         Deep exposure to digital advertising / monetization metrics — impressions, clicks, CTR, CPM, CPC, CVR, ROAS, revenue attribution, incrementality — is strongly preferred
• ·         Prior 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
• ·         Prior experience as a Staff / Principal Analytics Engineer, Staff Data Analyst, or Analytics Tech Lead at a top-tier tech company
• ·         Experience with A/B testing platforms and complex experimentation analysis (variance reduction, quasi-experiments, incrementality)
• ·         Solid statistics foundation (hypothesis testing, confidence intervals, regression basics) — enough to challenge a Data Scientist's methodology
• ·         Experience with data catalogs, lineage tools, or metric layer platforms (Amundsen, DataHub, Atlan, Cube, Transform, etc.)
• ·         Experience contributing to internal analytics platform / tooling improvements
• ·         Tableau certification (Certified Associate or Professional) or equivalent
• ·         Prior contract or fractional-lead experience with US-based tech companies

Benefits

• Remote work arrangement

Company Overview

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