Data Engineer

Job Title: Data Engineer Duration: 6+ Months Location: Princeton, NJ (Hybrid) Job Description:

• The Data Lake team is responsible for data ingestion from internal source systems in batch/real-time modes, curation and governance of the data assets created in the platform. The team also owns and maintains the existing ETL pipelines in Informatica and also works towards converting those to ELT by leveraging the Databricks product. The team has a broad and expert knowledge on Ratings organization's critical data domains, technology stacks and architectural patterns, fosters knowledge sharing and collaboration that results in a unified strategy.
• The Impact: You will be an expert contributor and part of the Rating Organization's Data Services Product Engineering Team with a unique opportunity to build and evolve S&P Ratings next gen data and analytics platform.

Our Hiring Manager Says

• If you are an individual that brings demonstrated experience of delivering big data projects as a data engineer, this is an excellent opportunity. We are looking for someone who has in-depth technical knowledge around data lake systems, is completely hands-on and worked on transformational initiatives for the business.

Responsibilities:

• Design & Build data pipelines with an emphasis on scale, performance and reliability.
• Provide technical expertise in the areas of design and implementation of Data Lake solution powered by Databricks on AWS cloud.
• Ensure data governance principles adopted, data quality checks and data lineage implemented in each hop of the data
• Partner with the data teams, enterprise architecture organization to ensure best use of standards for the key data domains and use cases
• Continuous learner with an eye on emerging trends around data lake architecture and enterprise data solutions.
• Ensure compliance through the adoption of enterprise standards and promotion of best practice / guiding principles aligned with organization standards
  
  
  Experience & Qualifications:
• BE, MCA or MS degree in Computer Science or Information Technology

For L4: 9+ years of experience programming with strong Java FS, Scala, Big Data.

• Experience is Big data eco system (Spark, Kafka, Delta Lake)
• Experience building streaming data pipelines using Kafka and Spark
• Development experience in delivering ELT/database/programming solution with hands on experience in big data concepts spark performance tuning, Data modeling and data ware housing concepts, Reusable transformations, Partition techniques.
• Strong knowledge on SQL optimizations and tuning.
• Must have experience in continuous delivery through CI/CD pipelines, containers and orchestration technologies.
• Preferred experience building data pipelines on Databricks, Snowflake, Azure Data Lake etc for Lakehouse/Warehouse solutions is an added advantage.
• Expert knowledge of Agile approaches to software development and able to put key Agile principles into practice to deliver solutions incrementally.
• Monitors industry trends and directions; develops and presents substantive technical recommendations to senior management
• Excellent analytical thinking, interpersonal, oral, and written communication skills with strong ability to influence both IT and business partners
• Ability to prioritize and manage work to critical project timelines in a fast-paced environment
• Financial services industry experience is an added advantage.
• Databricks experience or certifications is an added advantage.
• AWS or any public cloud certification is an added advantage.