Why this role stands out
As a Lead Full Stack Engineer at Business Intelli Solutions Inc, you'll architect and build cutting-edge marketing technology solutions, leveraging big-data and AI to drive impactful customer engagement. This on-site role is ideal for experienced engineers who thrive in a collaborative environment, enjoy technical leadership, and are eager to mentor teams and elevate engineering standards. You will have the opportunity to shape the future of MarTech and develop advanced skills in a dynamic setting.
Quick overview
Job description
Architect scalable, event-driven systems that power real-time marketing experiences and automated customer journeys.
Design and implement orchestration workflows using Adobe Campaign or equivalent enterprise-grade tools.
Develop high-performance big-data applications using Scala, Databricks, Spark SQL, Spark Streaming, and Python.
Build and optimize cloud-native data pipelines on Azure, including ADF-based ingestion, transformation, and orchestration.
Apply modern design patterns to ensure reliability, maintainability, and scalability across distributed systems.
Collaborate with product, marketing, and data teams to translate business needs into robust technical solutions.
Mentor engineers and elevate engineering standards, code quality, and operational excellence within the POD.
Strong proficiency in big-data technologies: Scala, Databricks, Spark SQL, Spark Streaming, Python.
Cloud engineering experience with Azure services, including Azure Data Factory.
Advanced system design capabilities including event-driven architectures and distributed design patterns.
Experience with AI-augmented development such as Vibe Coding or comparable frameworks.
Proven ability to lead engineering teams in a fast-paced, cross-functional environment.
Strong communication and stakeholder alignment skills with the ability to translate technical concepts into business impact.
Background in high-volume data processing supporting customer engagement or growth marketing.
Familiarity with DevOps practices including CI/CD, observability, and automated testing.
Exposure to modern AI/ML pipelines for personalization, segmentation, or content automation.
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