Senior Data Architect

[{"Salary":null , "Posting_Title":"Senior Data Architect" , "Is_Locked":false , "City":"Bangalore" , "Role_Overview":"Own and drive the end-to-end architecture of Finance data platforms, including scalable data models and robust ETL/ELT pipelines. Ensure high-quality, reliable, and auditable financial data through strong governance and engineering best practices. Provide technical leadership and collaborate cross-functionally to align data strategy with business and reporting needs.","Industry":"Financial Services","Job_Description":"

Responsibilities

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.