Senior Software Engineer- Python, Pyspark

Job Description

S&P Dow Jones Indices is seeking a Python/Bigdata developer to be a key player in the implementation and support of data Platforms for S&P Dow Jones Indices. This role requires a seasoned technologist who contributes to application development and maintenance. The candidate should actively evaluate new products and technologies to build solutions that streamline business operations. The candidate must be delivery-focused with solid financial applications experience. The candidate will assist in day-to-day support and operations functions, design, development, and unit testing. Responsibilities and Impact: Lead the design and implementation of EMR Spark workloads using Python, including data access from relational databases and cloud storage technologies. Implement new powerful functionalities using Python, Pyspark, AWS and Delta Lake. Independently come up with optimal designs for the business use cases and implement the same using big data technologies. Enhance existing functionalities in Oracle/Postgres procedures, functions. Performance tuning of existing Spark jobs. Respond to technical queries from operations and product management team. Implement new functionalities in Python, Spark, Hive. Enhance existing functionalities in Postgres procedures, functions. Collaborate with cross-functional teams to support data-driven initiatives. Mentor junior team members and promote best practices. Respond to technical queries from the operations and product management team. What Were Looking For: Basic Required Qualifications: Bachelors degree in computer science, Information Systems, or Engineering, or equivalent work experience. 5 - 8 years of IT experience in application support or development. Hands on development experience on writing effective and scalable Python programs. Deep understanding of OOP concepts and development models in Python. Knowledge of popular Python libraries/ORM libraries and frameworks. Exposure to unit testing frameworks like Pytest. Good understanding of spark architecture as the system involves data intensive operations. Good amount of work experience in spark performance tuning. Experience/exposure in Kafka messaging platform. Experience in Build technology like Maven, Pybuilder. Exposure with AWS offerings such as EC2, RDS, EMR, lambda, S3,Redis. Hands on experience in at least one relational database (Oracle, Sybase, SQL Server, PostgreSQL). Hands on experience in SQL queries and writing stored procedures, functions. A strong willingness to learn new technologies. Excellent communication skills, with strong verbal and writing proficiencies. Additional Preferred Qualifications: Proficiency in building data analytics solutions on AWS Cloud. Experience with microservice and serverless architecture implementation.