Key Responsibilities :

1. Define and design enterprise-scale data architectures for CDP AND CRM, MarTech ecosystem.

2. Develop canonical data models (Customer 360), identity resolution strategies, and consent frameworks.

3. Architect data ingestion pipelines (batch, streaming, APIs, CDC) ensuring data quality, governance, and interoperability.

4. Lead build vs. buy vs. hybrid assessments and guide platform/tool evaluations across AWS, Azure, and hybrid cloud environments.

5. Define governance processes for metadata management, lineage, observability, and access control.

6. Collaborate with stakeholders to enable AI/ML-driven personalization, predictive analytics, and reporting.

Must-Have Technical Skill :

1. Data Modeling : Canonical modelling (Delta Lake, Iceberg, Hudi), identity resolution frameworks.

2. Data Integration : Strong understanding of batch, real-time, API, and CDC pipelines.

3. Cloud Architecture : Expertise in AWS (Redshift, Glue, Kinesis, S3), Azure (Synapse, Data Factory, Event Hub), or equivalent.

4. Performance Optimization : Proven ability to design high-performance data pipelines, optimize queries, and reduce latency.

5. Documentation : Ability to produce clear, structured technical documentation for models, data flows, and governance.

6. Programming & Querying : Python (advanced), SQL (advanced), PySpark

Good-to-Have :

1. NoSQL databases (MongoDB, Cassandra, DynamoDB).

2. Data governance tools (Azure purview, Collibra etc.).

3. AI/ML integration (MLflow, AWS SageMaker, Azure ML etc.)