Role Overview:

We are looking for a highly skilled Data Architect with a deep understanding of modern data architectures to support a large-scale Data Warehouse to Data Lakehouse Transformation initiative for a leading banking client. The ideal candidate will have a strong background in data platform architecture, solution design, and implementation, with expertise in Cloudera, Teradata, and Informatica, and a solid understanding of banking data domains.

This role will play a pivotal part in designing scalable, secure, and high-performance data solutions that align with the bank’s enterprise data strategy.

Key Responsibilities:

• Design and define the end-to-end architecture for the Data Lakehouse solution covering Bronze, Silver, and Gold layers, metadata management, and data governance.
• Lead data platform modernization initiatives involving migration from legacy DWH to modern Cloudera-based architecture.
• Translate business and functional requirements into scalable data architecture solutions.
• Collaborate with engineering, platform, analytics, and business teams to define data flows, ingestion strategies, transformation logic, and consumption patterns.
• Ensure architectural alignment with enterprise data standards, security guidelines, and regulatory requirements.
• Define data modeling standards and oversee data modeling efforts across layers (relational and big data).
• Partner with the implementation oversight partner to review and validate logical and physical data models.
• Drive architecture reviews, performance tuning, and capacity planning for the data ecosystem.
• Guide and mentor data engineering teams on architectural best practices.

Required Skills and Experience:

• 12+ years of experience in data architecture, data platform design, or enterprise architecture roles.
• Strong hands-on experience in Cloudera (Hadoop ecosystem, Hive, HDFS, Spark), Teradata, Informatica PowerCenter/IDQ, and SQL-based platforms.
• Deep understanding of data ingestion, curation, transformation, and consumption in both batch and near real-time.
• Banking industry experience with familiarity across domains such as retail, corporate banking, credit risk, finance, and regulatory reporting.
• Proficiency in designing for scalability, performance optimization, and data security/compliance.
• Solid experience with data lakehouse concepts, open table formats (Iceberg/Delta), and layered architectures.
• Experience integrating BI/reporting platforms (e.g., Power BI, Cognos) and downstream data products.

Preferred Attributes:

• Experience with Kafka/NiFi for streaming ingestion and orchestration tools like Control-M or Airflow.
• Knowledge of metadata, lineage, and data catalog tools.
• Familiarity with hybrid deployment models (on-prem and cloud) and DevOps/DataOps pipelines.
• TOGAF, CDMP, or DAMA certification is a plus.