Lead Analytics Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Act as the primary analytics contributor for the Monetization Analytics team.

• Collaborate with Data Scientists and Product leaders on complex and ambiguous analytical challenges.

• Transform vague requests into more precise analytical strategies.

• Oversee comprehensive analytics projects that encompass data modeling, pipeline development, dashboard creation, and implementation.

• Establish standards and metrics for advertising revenue, monetization effectiveness, funnel/cohort metrics, and experimental evaluations.

• Conduct root-cause analyses on discrepancies found across dashboards, data warehouses, and pipelines.

• Mentor and support other analysts and analytics engineers.

• Design and manage production SQL pipelines, data models, data cubes, aggregate tables, and semantic layers.

• Create and maintain Airflow DAGs for revenue and monetization pipelines, ensuring SLAs, on-call support, backfills, and incident response are in place.

• Set data quality, reconciliation, and observability standards.

• Enhance pipeline efficiency for cost and latency on datasets exceeding one billion rows.

• Contribute to decisions regarding data platform design, schema alterations, migrations, design documentation, and reviews.

• Manage executive and cross-functional dashboards using Tableau and/or Superset.

• Regulate metric definitions, ownership, source-of-truth queries, validation, and deprecation processes.

• Facilitate self-service analytics through comprehensive documentation, certified metrics, sensible defaults, and coaching.

⛳️ Requirements

• Over 9 years of combined experience in Data Analytics, Business Intelligence, or Analytics Engineering roles.

• Minimum of 3 years at a Senior level or higher in an analytics-related role within a high-scale tech, ads-tech, marketplace, or fintech organization.

• Previous experience as the lead analytics individual contributor on an embedded team or a compelling case for transitioning into that role.

• Proven track record of managing end-to-end analytics projects from an ambiguous business question to data modeling, pipeline creation, dashboard implementation, and rollout.

• Direct experience collaborating with US-based Data Science, Product, and Engineering leaders as a fully engaged contributor.

• Expert-level SQL skills, including window functions, CTEs, complex joins, query optimization, incremental patterns, skew mitigation, and cost tuning on datasets with over a billion rows.

• Extensive hands-on experience with at least two of the following: Presto, Trino, Hive, Spark SQL, Snowflake, BigQuery, or Redshift.

• Advanced experience with Airflow, including managing large DAG ecosystems, cross-DAG dependencies, large-scale backfills, and SLA oversight; experience with equivalent orchestrators is also acceptable.

• Expertise in data architecture and modeling, including Kimball, star schema, dimensional modeling, OLAP cubes, wide fact tables, slowly-changing dimensions, and semantic layer design.

• Background in ETL/ELT architecture, including incremental loads, backfills, idempotency, data quality frameworks, and data lineage.

• Proficiency in Python for data tasks, including pandas, PySpark, scripting, and basic tool development.

• Experience with dbt or an equivalent transformation framework is highly preferred.

• Involvement in or review of design documents and RFCs for data platforms and pipelines is essential.

• Significant experience creating executive-level dashboards in Tableau and/or Apache Superset; familiarity with Looker, Power BI, or Mode is also acceptable.

• Proven ability to drive metric governance and self-service BI at an organizational level.

• Strong understanding of KPI definition, metric design, funnel analysis, cohort analysis, and A/B testing methodologies.

• Extensive knowledge of digital advertising and monetization metrics is strongly preferred.

• Fluent or nearly fluent in English, both spoken and written — a strict requirement.

• A history of leading initiatives from start to finish with minimal guidance.

• Experience in mentoring or coaching junior analysts and analytics engineers.

• Capability to present analytics findings to Director/VP-level stakeholders and defend recommendations effectively.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible work hours and remote work options.

• Opportunities for professional growth and development.

• Engaging and inclusive company culture.