Data Architect/Technology Architect

Job Description

We are looking for a Data Architect to design, build, and operate scalable data pipelines and data products, enabling a modern data mesh architecture.

The role focuses on integrating Legacy systems with cloud-native platforms to support analytics, reporting, and domain-owned data products.

Primary Skills

• Strong experience with Databricks (Spark, PySpark/SQL) and data lake architectures.
• Hands-on experience with streaming technologies, especially Kafka/Confluent Kafka.
• Experience integrating Legacy data sources such as DB2 (Mainframe) and SQL Server.
• Working knowledge of AWS data services, especially S3.
• Understanding of data product thinking, data mesh concepts, and modern data engineering best practices.

Key Responsibilities

• Build and maintain batch and streaming data pipelines from Legacy Mainframe DB2 and on prem SQL Server systems into an AWS-based data lake.
• Implement Real Time ingestion using Confluent Kafka and land data in Client S3.
• Develop data transformations and analytics pipelines in Databricks using the medallion architecture (Bronze, Silver, Gold).
• Design and deliver high-quality, reusable data products aligned to data mesh principles.
• Ensure data quality, reliability, security, and governance across pipelines.
• Collaborate with domain teams, platform teams, and stakeholders to enable self-serve analytics and consumption.

Good to have

• Experience in banking or financial services data platforms.
• Familiarity with data governance, metadata management, and regulatory reporting