SabPaisa - Data Modeler/Architect

Job Summary

We are looking for a skilled Data Modeler / Architect with 58 years of experience in designing, implementing, and optimizing robust data architectures in the financial payments industry.The ideal candidate will have deep expertise in SQL, data modeling, ETL/ELT pipeline development, and cloud-based data platforms such as Databricks or Snowflake. You will play a key role in designing scalable data models, orchestrating reliable data workflows, and ensuring the integrity and performance of mission-critical financial datasets.This is a highly collaborative role interfacing with engineering, analytics, product, and compliance teams.

Key Responsibilities

• Design, implement, and maintain logical and physical data models to support transactional, analytical, and reporting systems.
• Develop and manage scalable ETL/ELT pipelines for processing large volumes of financial transaction data.
• Tune and optimize SQL queries, stored procedures, and data transformations for maximum performance.
• Build and manage data orchestration workflows using tools like Airflow, Dagster, or Luigi.
• Architect data lakes and warehouses using platforms like Databricks, Snowflake, BigQuery, or Redshift.
• Enforce and uphold data governance, security, and compliance standards (e.g., PCI-DSS, GDPR).
• Collaborate closely with data engineers, analysts, and business stakeholders to understand data needs and deliver solutions.
• Conduct data profiling, validation, and quality assurance to ensure clean and consistent data.
• Maintain clear and comprehensive documentation for data models, pipelines, and architecture.
  

Required Skills & Qualifications

• 58 years of experience as a Data Modeler, Data Architect, or Senior Data Engineer in the financial/payments domain.
• Advanced SQL expertise, including query tuning, indexing, and performance optimization.
• Proficiency in developing ETL/ELT workflows using tools such as Spark, dbt, Talend, or Informatica.
• Experience with data orchestration frameworks: Airflow, Dagster, Luigi, etc.
• Strong hands-on experience with cloud-based data platforms like Databricks, Snowflake, or equivalents.
• Deep understanding of data warehousing principles: star/snowflake schema, slowly changing dimensions, etc.
• Familiarity with financial data structures, such as payment transactions, reconciliation, fraud patterns, and audit trails.
• Working knowledge of cloud services (AWS, GCP, or Azure) and data security best practices.
• Strong analytical thinking and problem-solving capabilities in high-scale environments.
  

Preferred Qualifications

• Experience with real-time data pipelines (e.g., Kafka, Spark Streaming).
• Exposure to data mesh or data fabric architecture paradigms.
• Certifications in Snowflake, Databricks, or relevant cloud platforms.
• Knowledge of Python or Scala for data engineering tasks
  

(ref:hirist.tech)