Lead AIML Data Engineer // only local to NJ // 15+ EXPERIENCE
CloudIngest, Berkeley Heights, NJ, United States
Role Overview
We are seeking an AI/ML Data Engineer with strong expertise in Power BI and dashboard development to support internal project management and product data initiatives. The ideal candidate will combine data engineering skills with business intelligence expertise, enabling actionable insights through scalable data pipelines and intuitive dashboards.
Key Responsibilities
Design, build, and optimize data pipelines to support AI/ML models and analytics.
Develop and maintain Power BI dashboards for project management and product data reporting.
Collaborate with product managers, project leads, and business stakeholders to gather requirements and translate them into data solutions. Data engineering with exposure to AI/ML workflows.
Strong hands-on expertise with Power BI (data modeling, DAX, dashboard design).
Experience with Databricks optimizations, Delta tables, and serverless architectures.
Proficiency in SQL, Python, and Spark for data processing.
Knowledge of cloud platforms (AWS, Azure, GCP) and hybrid environments.
Familiarity with Kafka, streaming ingestion, and batch pipelines.
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We are seeking an AI/ML Data Engineer with strong expertise in Power BI and dashboard development to support internal project management and product data initiatives. The ideal candidate will combine data engineering skills with business intelligence expertise, enabling actionable insights through scalable data pipelines and intuitive dashboards.
Key Responsibilities
Design, build, and optimize data pipelines to support AI/ML models and analytics.
Develop and maintain Power BI dashboards for project management and product data reporting.
Collaborate with product managers, project leads, and business stakeholders to gather requirements and translate them into data solutions. Data engineering with exposure to AI/ML workflows.
Strong hands-on expertise with Power BI (data modeling, DAX, dashboard design).
Experience with Databricks optimizations, Delta tables, and serverless architectures.
Proficiency in SQL, Python, and Spark for data processing.
Knowledge of cloud platforms (AWS, Azure, GCP) and hybrid environments.
Familiarity with Kafka, streaming ingestion, and batch pipelines.
#J-18808-Ljbffr