Data Engineer – SQL/Python

Job Description

Kaleidofin is a fintech focused on the goal to unlock access to tailored finance for women, agriculture and nano entrepreneurs. We provide the ki credit platform, combining credit health assessment (ki score), middleware rails and best-in-class risk management (ki view) to enable the financial ecosystem to better serve customers. By building credit health scores for impactful finance and innovating on debt structures that scale inclusion, Kaleidofin is achieving this goal in India, Bangladesh and East Africa and expanding.
You Will

Build large scale, highly available, fault tolerant data analytics platforms & data pipelines that horizontally scale and can support advanced analytics including modelling and machine learning.
Work in a fully agile environment by completing deliverables on time with a high amount of quality.
Design and develop products by collaborating/influencing business and data science teams.
Independently own components and co-own applications with other developers by reviewing design documents, (peer) reviewing code, providing design direction and guidance.
Establish strong data engineering best practices and champion their adoption.

Who you need to be?

2+ years’ experience in software product development and delivery
Bachelors or Masters degree in engineering (preferably computer science or sister branches) from a reputed institute (preferably IITs, NITs, or other top engineering institutes)
All experience should be from good product development or e-commerce background.
Must have shown good stability in all your previous associations.
Strong grasp of CS fundamentals like OS, algorithms and excellent problem- solving abilities – Prior experience in building and supporting highly scalable & resilient databases, warehouses, data pipelines etc and co-ordination with data scientists in consumption for analytics.

Skill Set Mandatory

Have strong data engineering knowledge and cloud development exposure.
Proficiency in python, SQL, (py)Spark, Cassandra, AWS data pipeline stack (Athena, S3, Glue data catalog etc. ), Airflow.
Proficiency in both RDBMS (Mysql preferred) and NoSql datastores.
Very comfortable with data lakes, warehouses, ETL/ELT paradigms and various latest data engg architectures.
Worked in an agile development environment.

Optional

Basic knowledge of statistical analysis, mathematical modelling and machine learning – Experience with cloud technologies
Microservices, Docker, Kubernetes, Gradle, Kafka, GIT, unit/integration tests, Grafana, Kibana, Jira, Prometheus, Redis

Job location – Bangalore (work from office-Hybrid)