Data Engineer

A global, value-oriented, and event-driven hedge fund specializing in healthcare and consumer-goods industries is looking for a Data Engineer. The selected candidate will be working with a team of experienced engineers and responsible for various tasks to build a scalable product. The US-based company invests predominantly in equities and can be opportunistic across the capital structure. This is a great opportunity for developers who enjoy tackling complex compelling data and problems. This role requires some overlap with the EST time zone. 

Job Responsibilities:

• Design database and data pipeline/ETL using emerging technologies and tools
• Motivate the team to develop sound analytic solutions
• Define standards and methodologies for the Data Warehousing environment
• Design and build highly scalable data pipelines 
• Leverage new generation tools and technologies like AWS, Snowflake, Spark, Kafka to induct data from various systems
• Translate complex business requirements into scalable technical solutions 
• Build scalable data pipelines and ETL applications that support business operations
• Assist with deciphering data migration issues and improving system performance
• Collaborate efficiently with product management, technical program management, operations, and other engineers

Job Requirements:

• Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
• At least 3+ years of relevant experience as a Data Engineer
• Must possess professional experience working languages like Python
• Should be familiar with Pandas and SQL connectors along with knowledge of parsing files, writing classes, and common libraries
• Should be capable of working with technologies like SQL along with an understanding of s3, EFS, awscli, boto3, EC2, EMR, and Batch
• Ability to contribute to ETL pipeline processes
• Knowledge of writing modular codes to improve unit tests
• Ability to work with technologies like Docker and Apache Airflow is required