Sr. Data Platform Engineer

Senior Data Engineer / Senior Data Platform Engineer – Audience Engine

Pay
Hourly rate: $85 - $95

Location
Hybrid (Midtown Manhattan)

Summary
We are seeking a highly skilled Senior Data Engineer to take ownership of a newly developed data platform. This role is pivotal in ensuring the platform’s operational stability, cost efficiency, and scalability. The successful candidate will serve as the primary internal steward of data ingestion, identity resolution, automation, and AI enablement, supporting the organization’s long-term growth. This position offers an opportunity to work on innovative AI capabilities and to shape the future of data-driven marketing and analytics within the organization.

Requirements

• 6+ years of experience as a Data Engineer or Data Platform Engineer, preferably in advertising, identity, or large-scale data environments
• Hands-on expertise with Databricks, Spark, and cloud data platforms
• Proven experience in building and maintaining multi-layer data architectures (Bronze/Silver/Gold)
• Strong experience working with identity graphs, audience data, and complex join logic
• Proficiency in SQL and at least one scripting language (Python preferred)
• Experience managing third-party data integrations and automated pipelines
• Practical knowledge of AI/ML platforms and AI-enabled analytics tools
• Demonstrated ability to design, test, and refine prompts for structured data analysis and predictive modeling
• Understanding of data quality, schema design, feature engineering, and their impact on AI models

Responsibilities

• Own and maintain data pipelines supporting audience ingestion, enrichment, and activation
• Monitor and troubleshoot ingestion failures, schema drift, and data quality issues
• Optimize pipeline performance and cloud cost management strategies
• Oversee identity resolution and maintain household identity graphs through deterministic and probabilistic matching
• Support and maintain integrations with various activation and enrichment partners
• Collaborate on onboarding new data sources and destinations
• Support AI workflows, including prompt engineering and operationalizing AI outputs
• Enforce data governance standards, privacy policies, and lineage tracking
• Provide clean and query-ready datasets for BI reporting, audience insights, and predictive analytics
• Partner with analytics teams to ensure data structures meet reporting and AI needs
• Contribute to platform reliability through monitoring, alerting, and documentation

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