Required Skills & Experience
- 10+ years of experience in Data Engineering with 5+ years of leadership experience managing Data Engineers, Technical Leads and third party team
- Strong experience designing and operating modern cloud data platforms utilizing technologies AWS Kinesis, Kafka, Apache Flink, Flink, Lamndas,
- Deep understanding of ETL/ELT pipelines, data modeling, orchestration, APIs, event-driven architectures, streaming data technologies, observability, data quality, and operational support
- Experience building and managing batch and real-time data pipelines that support analytics, reporting, personalization, customer insights, and business intelligence initiatives
- Experience integrating with Customer Data Platforms (CDPs) and identity solutions
- Experience with streaming data technologies such as Apache Kafka, Apache Flink, AWS Kinesis, Pub/Sub, or comparable tools
- Experience supporting entertainment, OTT, SVOD, AVOD, FAST, subscription-based including playback events, content engagement, subscriber funnels, churn and customer lifecycle
- Strong knowledge of data governance, privacy, security, consent management, and compliance best practices related to data collection, storage, activation, and retention
- Proficiency with Python, Java, Scala, SQL, or other data-focused programming languages
Nice to Have Skills & Experience
- Familiarity with analytics, visualization, and observability platforms such as Amplitude, Google Analytics, Conviva, Tableau, Looker, Power BI, Mux, or Youbora
- Experience supporting personalization, recommendation engines, experimentation platforms, audience segmentation, marketing activation, or machine learning initiatives
- Experience with data catalogs, lineage tools, metadata management, consent management platforms, and privacy-focused data ecosystems
Job Description
Insight Global is seeking a Director of Data Engineering to lead the strategy, architecture, and operational excellence of a modern data platform supporting a large scale streaming and subscription business. This individual will oversee Data Engineers, Analytics Engineers, and technical partners responsible for building scalable batch. On a day-to-day basis, they will partner closely with Product, Engineering, Marketing, Finance, Data Science, Privacy, and Security teams to define data roadmaps, establish governance standards, improve analytics instrumentation, and ensure data quality across the organization. They will drive modernization efforts by implementing cloud-native data solutions, improving observability and reliability, optimizing platform performance, and enhancing self-service analytics capabilities. The ideal candidate will bring a combination of strong technical leadership, data platform expertise, and experience building scalable data ecosystems that support customer growth, engagement, retention, and operational efficiency.