Senior Financial Data Architect

2 weeks ago

Mumbai, Maharashtra, India beBeeData Full time ₹ 20,00,000 - ₹ 30,00,000
Job Description

We are seeking a highly skilled Senior Data Engineer to join our organization. As a key member of our data engineering team, you will be responsible for designing, building, and maintaining scalable data pipelines for processing financial data.

Our ideal candidate will have a strong understanding of financial products and the loan lifecycle from origination to closure.

Key Responsibilities:

  • Design and develop complex data pipelines for processing financial data across functions like loan origination, disbursement, collection, and regulatory reporting.
  • Develop and optimize ETL workflows to extract data from core banking systems, loan management platforms, payment gateways, credit bureaus, and other sources.
  • Perform complex data blending and transformation to merge internal financial datasets with external credit scores, market data, and compliance-related information.
  • Ensure data quality, consistency, and regulatory compliance through robust transformation logic and validations.
  • Build and maintain data warehouse architectures, including cloud-based solutions.
Technical Requirements

Our ideal candidate will have hands-on experience with:

  • Proficiency in SQL, Python, and/or Scala for advanced data processing.
  • ETL tools like Informatica, Talend, SSIS, or similar.
  • Modern data warehousing platforms such as Snowflake, Amazon Redshift, Google BigQuery, or traditional enterprise DWH systems.
  • Big data technologies Hadoop, Apache Spark, Kafka.
  • Cloud platforms such as AWS, Azure, or Google Cloud.
Domain Expertise

A strong understanding of financial products and the loan lifecycle from origination to closure is required.

Qualifications
  • Experience in real-time data streaming and event-driven data architectures.
  • Familiarity with data governance frameworks, data lineage, and metadata management tools.
  • Certifications in cloud platforms (AWS, Azure, GCP) or data engineering tools.
  • Understanding of machine learning workflows related to credit scoring or risk assessment.

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