Intern - Data Engineer

As a Data Engineer / Analytics Engineer at bluCognition, you will be part of an AI/ML based start-up specializing in risk analytics, data conversion, and data enrichment capabilities. Founded in 2017 by senior professionals from the financial services industry, bluCognition is headquartered in the US with a delivery center based in Pune. Leveraging the latest technology stack in AI, ML, and NLP, combined with decades of experience in risk management, we cater to some of the biggest names in the financial services industry. Role Overview: - Work with large structured datasets using SQL and PySpark. - Build, maintain, and optimize ETL/data processing pipelines. - Assist in business/entity matching logic and fuzzy matching implementations. - Create and validate analytical datasets for model development and reporting. - Perform data cleaning, transformation, aggregation, and quality checks. - Write efficient SQL queries using joins, CTEs, window functions, and aggregations. - Support feature engineering for ML/risk modeling use cases. - Work on incremental data processing and monthly/daily refresh strategies. - Analyze data discrepancies, debug pipeline failures, and improve reliability. - Collaborate with analytics, data science, and engineering teams. - Participate in testing, deployment, and code review activities. Key Responsibilities: - Background in Computer Science, Data Science, Statistics, Mathematics, or related field. - Strong SQL knowledge including joins, CTEs, aggregations, CASE statements, and window functions. - Basic understanding of Python and familiarity with PySpark or distributed data processing concepts. - Understanding of relational databases, data structures, and ETL/data pipeline concepts. - Exposure to AWS or cloud platforms such as Redshift, Spark, Hadoop, or Databricks is a plus. - Familiarity with Git/version control and basic understanding of APIs. - Analytical mindset, strong problem-solving skills, attention to detail, and data accuracy. - Ability to work in a fast-paced environment and deal with ambiguity. - Strong communication, documentation, and collaboration skills across multiple teams. In this role, you will play a crucial part in the growth phase of bluCognition, contributing your analytical skills and motivation to the team. Join us in this exciting journey and be a part of our innovative solutions in the financial services industry. As a Data Engineer / Analytics Engineer at bluCognition, you will be part of an AI/ML based start-up specializing in risk analytics, data conversion, and data enrichment capabilities. Founded in 2017 by senior professionals from the financial services industry, bluCognition is headquartered in the US with a delivery center based in Pune. Leveraging the latest technology stack in AI, ML, and NLP, combined with decades of experience in risk management, we cater to some of the biggest names in the financial services industry. Role Overview: - Work with large structured datasets using SQL and PySpark. - Build, maintain, and optimize ETL/data processing pipelines. - Assist in business/entity matching logic and fuzzy matching implementations. - Create and validate analytical datasets for model development and reporting. - Perform data cleaning, transformation, aggregation, and quality checks. - Write efficient SQL queries using joins, CTEs, window functions, and aggregations. - Support feature engineering for ML/risk modeling use cases. - Work on incremental data processing and monthly/daily refresh strategies. - Analyze data discrepancies, debug pipeline failures, and improve reliability. - Collaborate with analytics, data science, and engineering teams. - Participate in testing, deployment, and code review activities. Key Responsibilities: - Background in Computer Science, Data Science, Statistics, Mathematics, or related field. - Strong SQL knowledge including joins, CTEs, aggregations, CASE statements, and window functions. - Basic understanding of Python and familiarity with PySpark or distributed data processing concepts. - Understanding of relational databases, data structures, and ETL/data pipeline concepts. - Exposure to AWS or cloud platforms such as Redshift, Spark, Hadoop, or Databricks is a plus. - Familiarity with Git/version control and basic understanding of APIs. - Analytical mindset, strong problem-solving skills, attention to detail, and data accuracy. - Ability to work in a fast-paced environment and deal with ambiguity. - Strong communication, documentation, and collaboration skills across multiple teams. In this role, you will play a crucial part in the growth phase of bluCognition, contributing your analytical skills and motivation to the team. Join us in this exciting journey and be a part of our innovative solutions in the financial services industry.