About the Position

We are seeking a Data Solution Architect to design and implement scalable, cloud-native data solutions across both OLAP (analytical) and OLTP (operational) architectures, applying advanced data management and governance practices within a large-scale banking environment. This role provides technical leadership on modern data platforms - spanning Data Lakes, Operational Data Stores, real-time streaming, and Data Mesh - ensuring solutions are secure, performant, cost-optimised, and aligned with enterprise data strategy. The successful candidate will combine deep data engineering expertise with architectural vision, working across business, data engineering, and analytics teams to deliver data solutions that support both operational excellence and advanced analytics use cases.

Responsibilities

Design Data Lake and Operational Data Store architectures using cloud-native technologies to support both analytical (OLAP) and operational (OLTP) workloads, ensuring proper separation, scalability, and performance.
Define and enforce Data Mesh principles for decentralized data ownership and governance, establishing domain-oriented data products, self-serve data infrastructure patterns, and federated governance.
Develop conceptual, logical, and physical data models for analytical and operational use cases, ensuring models are well-documented, fit for purpose, and aligned with enterprise data standards.
Design batch and real-time data ingestion pipelines using Apache Kafka and other streaming technologies, ensuring reliable, low-latency data flow from source systems to Data Lakes, ODS, and downstream consumers.
Build and manage scalable ETL/ELT processes for data cleansing, validation, transformation, and enrichment across multiple source systems including core banking, payments, and transaction banking platforms.
Define patterns for data pipeline orchestration, error handling, retry logic, and monitoring to ensure production-grade reliability and observability.
Utilize AWS services such as S3, Glue, Redshift, Lambda, Kinesis, Airflow, and SageMaker to deliver end-to-end cloud-native data solutions aligned with security, cost optimization, and scalability principles.
Support advanced analytics and machine learning use cases by designing data pipelines and platform capabilities that provide governed, high-quality data to data science and business intelligence teams.
Implement data quality frameworks incorporating validation, profiling, and anomaly detection to ensure data trustworthiness.
Establish and maintain metadata management and data lineage tracking to provide transparency into data origins, transformations, and usage.
Define data standards, policies, and best practices collaboratively with data owners, compliance, and business stakeholders to align with regulatory and governance frameworks.
Collaborate with data product owners, data engineers, analytics teams, and business stakeholders to understand requirements, define data products, and deliver solutions driving measurable business value.

Requirements

Must Have

Expertise in data architecture and engineering within large-scale enterprise settings, focusing on designing and implementing complex data platforms.
Proficiency in real-time data streaming with Apache Kafka.
Skilled in AWS data service platforms for end-to-end cloud-native solutions.
Strong data modeling across various schema designs and workloads.
Analytical problem-solving for complex distributed data systems.
Effective communication and stakeholder engagement.
Domain knowledge in commercial banking transaction services.

Nice to Have

Advanced knowledge in data governance and data quality frameworks.
Experience with other cloud platforms (e.g., Azure, Google Cloud).

We Offer

Competitive salary
Opportunity to work in a dynamic and innovative environment
Professional growth and development opportunities

About the Company

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Application

Apply for Data Solution Architect in Gurugram, India.

Data Solution Architect

Job description