Senior Data Engineer

4 weeks ago

Mumbai, India Catalyst IQ Full time

Key Responsibilities :


- Design, build, and maintain scalable 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 (e.g., Snowflake, Redshift, BigQuery).


- Collaborate closely with teams in finance, risk management, underwriting, and compliance to align data models and outputs with business needs.


- Implement data validation frameworks and monitoring systems to guarantee data accuracy for internal use and regulatory reporting.


- Tune and optimize query performance for large-scale datasets, improving data accessibility and processing Skills :


- Proficiency in SQL, Python, and/or Scala for advanced data processing.


- Hands-on experience with ETL tools like Informatica, Talend, SSIS, or similar.


- Experience with modern data warehousing platforms such as : Snowflake, Amazon Redshift, Google BigQuery, or traditional enterprise DWH systems.


- Knowledge of big data technologies : Hadoop, Apache Spark, Kafka.


- Working experience with cloud platforms such as AWS, Azure, or Google Cloud Knowledge :


- Strong understanding of financial products and the loan lifecycle from origination to closure.


- Familiarity with loan origination systems, collections processes, and credit risk evaluation.


- Knowledge of financial compliance and regulatory frameworks such as : RBI guidelines, CIBIL data formats, and other industry 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.

(ref:hirist.tech)

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