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Fluent is building the next-generation advertising network, Partner Monetize & Advertiser Acquisition. Our vision is to build an ML/AI-first network of advertisers and publishers to achieve a common objective — elevating relevancy in E-commerce for everyday shoppers. As our Engineering Manager - Data Platform & Analytics, you will lead the teams responsible for Fluent's data infrastructure and business intelligence capabilities. You will own the full data lifecycle from ingestion through reporting — managing our Data Engineering team that builds and maintains pipelines, and our Analytics/BI team that transforms data into actionable business insights. This role combines deep technical platform expertise with business acumen, requiring you to drive our Databricks platform strategy while ensuring the organization has reliable, high-quality data and reporting to make informed decisions.
Job Responsibility:
Own Databricks platform strategy: architecture decisions, Unity Catalog migration, cost optimization, and operational excellence
Drive data pipeline development: real-time and batch pipelines using PySpark, Spark Structured Streaming, and Delta Lake
Establish data quality standards: validation frameworks, monitoring, alerting, and SLA management
Partner with Data Architects to translate Enterprise Data Models into performant physical implementations
Integrate streaming infrastructure: Kafka-based event-driven ingestion and processing
Build reporting capabilities: dashboards, KPIs, and self-service analytics for internal and client-facing use
Drive data storytelling: executive presentations, client reporting, and strategic business insights
Develop metrics frameworks: campaign performance, audience quality, and platform health KPIs
Support ad-hoc analysis for campaign optimization and business questions
Lead and grow DE and Analytics teams: hiring, mentoring, performance management, and career development
Coordinate with offshore partners to extend team capacity and manage distributed development workflows
Partner cross-functionally with Data Science, Product, and Client Success to align data capabilities with business needs
Champion engineering best practices: code reviews, CI/CD, testing, documentation, and observability
Requirements:
6+ years of experience in Data Engineering or Analytics, with at least 2 years managing or leading teams
Deep Databricks expertise: Workflows, Delta Lake, Unity Catalog, and platform administration
Strong Spark experience: PySpark, Spark SQL, and understanding of distributed processing internals
Business intelligence expertise: dashboard development, KPI frameworks, and analytics tooling (Tableau, Looker, Power BI, or similar)
Experience with streaming architectures: Kafka, event-driven processing, and real-time pipelines
Proven people management skills: hiring, mentoring, performance management, and team development
AWS experience: S3, IAM, and cloud infrastructure fundamentals
Strong communication skills for partnering with technical and business stakeholders
Nice to have:
Ad tech or marketing tech data platform experience
Experience managing offshore or distributed engineering teams
Data governance and cataloging experience
Cost optimization experience for cloud data platforms
Client-facing analytics and reporting experience
Experience with medallion architecture (Bronze/Silver/Gold) patterns
What we offer:
Competitive compensation
Ample career and professional growth opportunities
New Headquarters with an open floor plan to drive collaboration
Health, dental, and vision insurance
Pre-tax savings plans and transit/parking programs
401K with competitive employer match
Volunteer and philanthropic activities throughout the year
Educational and social events
The amazing opportunity to work for a high-flying performance marketing company