Product Manager Enterprise Data Warehouse

BettingJobs is excited to present an exceptional opportunity in Ras Al Khaimah, UAE, for ambitious individuals looking to take on a career defining role.

Set to open in early 2027, our client is developing a landmark 72-floor resort in Ras Al Khaimah featuring a casino, hotel, multiple restaurants, and a marina.

In preparation for this, they are looking to add a Product Manager Enterprise Data Warehouse to their corporate team.

Responsibilities

• Define and drive the vision, strategy, and roadmap for the enterprise data platform.
• Champion modern data architectures (lakehouse, streaming pipelines, real-time analytics).
• Develop long-term strategies for data storage, processing, governance, and activation.
• Oversee end-to-end data pipelines (batch ingestion, real-time streaming, storage, transformation, activation).
• Ensure best practices in ETL/ELT, schema design, and data quality.
• Lead integration of real-time streaming technologies (Kafka, Flink, Confluent).
• Implement data governance (metadata management, lineage tracking, data cataloging).
• Ensure security and compliance (GDPR, CCPA, HIPAA).
• Standardize data quality and master data management (MDM).
• Collaborate with engineering, AI/ML, BI, marketing, and CRM teams for seamless data access.
• Support MLOps (model training, tracking, deployment) with platforms like Databricks and MLflow.
• Enable data activation via CRM integrations and omnichannel platforms.
• Optimize cloud compute resources (Azure) for cost and performance.
• Drive innovation in data storage, query optimization, and real-time analytics.
• Evaluate and implement new data technologies for scalability and efficiency.

Requirements

• 7 years of experience in product management, data engineering, or data platform architecture.
• Deep knowledge of data warehousing (Snowflake) and data lake solutions (Azure Data Lake, Delta Lake, Iceberg).
• Strong understanding of data engineering pipelines, ETL/ELT, and real-time streaming (Kafka, Flink, Spark, Databricks).
• Hands-on experience with data governance tools, data catalogs, and lineage tracking (Coalesce, Atlan, Alation).
• Familiarity with AI/ML platforms (Databricks, MLflow, Feature Stores, Auto
• ML) and their data dependencies.
• Strong experience in SQL, Python, and cloud-native data processing.
• Ability to bridge technical and business requirements, working cross-functionally across multiple teams.