We are seeking a Senior Data Architect to lead the architecture and design of Finance data platforms and data products at scale. This role will be responsible for defining data models, architecture patterns, governance standards, and scalable data pipelines that support financial operations, reporting, reconciliation, and analytics. The ideal candidate combines deep expertise in transactional and analytical data modeling with hands-on experience building large-scale data systems. They will partner closely with Finance, Risk, Engineering, Analytics, and Operations teams to translate business requirements into robust, maintainable, and scalable data solutions.

Position / Designation : Senior Data Architect - Finance Data

Qualification : Diploma / Any graduate

Years of Experience : 10+ years of experience in Data Architecture, Data Engineering, Data Warehousing, or related fields.

Employment Type : Fulltime / Permanent

Office Location : Bangalore - Bellandur

Selection Process :

1. Total 3 Technical rounds.

2. 2 rounds evaluation with LV (we can plan to take this together based on panel availability) & 1 with client.

Job Role & Responsibility :

Data Architecture & Modeling :

- Define and own the architecture for Finance data platforms and datasets.

- Design enterprise-grade transactional data models using MySQL and PostgreSQL.

- Design scalable analytical data models using Hive, Spark, and data warehouse technologies.

- Establish standards for fact, dimension, aggregate, historical, and reporting data structures.

- Define table grain, primary keys, partitioning strategies, indexing, retention policies, and historical tracking approaches.

- Design data contracts and integration patterns across Finance systems and downstream consumers.

Data Pipeline Architecture :

- Architect and guide the implementation of ETL/ELT pipelines supporting Finance use cases.

- Design scalable ingestion and processing patterns including batch, incremental, CDC, backfill, reconciliation, and recovery workflows.

- Ensure reliability, scalability, observability, and maintainability of data pipelines.

- Drive architecture decisions for performance optimization and cost efficiency.

Governance & Quality :

- Establish data quality, lineage, metadata, ownership, and governance standards.

- Define reconciliation frameworks and controls to ensure financial data accuracy and auditability.

- Drive best practices for monitoring, validation, and operational excellence.

- Partner with stakeholders to ensure compliance with financial reporting requirements.

Technical Leadership :

- Provide architectural guidance and design reviews across Finance data initiatives.

- Mentor engineers and data practitioners on modeling and architecture best practices.

- Collaborate with Finance, Engineering, Analytics, and Operations teams to align business and technical goals.

- Influence long-term data platform strategy and roadmap.

Skills :

- Strong expertise in both transactional (OLTP) and analytical (OLAP) data modeling.

- Deep hands-on experience with MySQL, PostgreSQL, Hive, and Spark.

- Expert-level SQL skills and strong understanding of distributed data processing.

- Experience designing large-scale ETL/ELT architectures and data platforms.

- Strong understanding of CDC, incremental processing, reconciliation, data quality, and metadata management.

- Experience working with Finance domains such as payments, settlements, accounting, ledgers, reconciliation, or financial reporting.

- Proven ability to drive architecture decisions and work independently as a senior technical leader.

- Experience with Spark SQL, PySpark, Hive SQL, Airflow, or similar orchestration frameworks.

- Experience designing data architectures in fintech, payments, marketplace, mobility, or large-scale technology environments.

- Exposure to data governance, cataloging, lineage, and observability platforms.

- Experience supporting audit, compliance, and financial controls requirements.

Joining Date : Immediate

Education : UG: Any Graduate

Key Skills : Hive, Hive SQL, Data Architecture, Spark, ETL, Airflow, PostgreSQL, MySQL