Senior Data Engineer - Associate

Morgan Stanley•New York, NY

2d•$90,000 - $150,000

About The Position

As a senior data engineer your role will be to create and deliver high quality, resilient data solutions to our Fraud business partners and being a productive member of the development team. You will be working on various existing and new technology stacks which include on-prem relational and big-data technologies & new cloud-based technologies in Azure. You will be expected to share ownership of our projects and contribute to the active development and maintenance of our applications. You will have the opportunity to be exposed to modern software engineering tools and best practices. You will have the opportunity to be exposed to how a large investment bank like Morgan Stanley detects and prevents fraud. You will work in a dynamic agile team that uses Scrum for its workflow. You will be expected to be involved in the full development lifecycle. You will be expected to collaborate with others in the wider team as well as working

Requirements

6+ years of relevant work experience
Strong with programming in Python to perform Batch data engineering on Apache Spark and populate downstream batch data stores (such as data mart) for BI use cases & to generate downstream feeds (ie., flat & wide tables or compressed files) for Data Science use cases
Real-time service integration to process business events off Kafka and persist in operational MS SQL/MongoDB and/or Neo4j Graph data stores for fraud investigation
Near real-time stream processing to derive features for ML model inference.
Strong with SQL Server & Hadoop based implementations
Strong SQL & Stored Procedure skills
Exposure to modern operational NewSQL or NoSQL database technologies such as Neo4j, MongoDB, MemSQL etc.,
Good hands-on experience with at least one of the job scheduling tools like Autosys (Preferred), Control-M etc.
Experience of working in a Linux environment and can write Python/Shell scripts
Strong data architecture and modeling experience. Especially, in dimensional modeling for data mart design and development to support BI use cases
Strong data analytics skills
Strong oral and written communication skills
Excellent interpersonal skills and professional approach
Strong analytical and problem-solving skills
Ability to learn quickly and pick up new techniques and/or technologies
Experience in building & maintaining data solutions for Operational, BI & Data Science use cases

Nice To Haves

Experience with Azure (Databricks, Data Factory, Synapse, Azure Data Lake) and/or AWS (AWS S3, AWS Athena, AWS Glue) Data ecosystem & Snowflake Data Cloud
Experience in building virtual data access layer using Data Virtualization technologies to support BI & Data Science use cases
Experience of the full software development life cycle
Experience of working in an Agile team
Experience of working with version control systems
Experience with bash scripting
Experience of working with Continuous Integration systems
Experience in Fraud detection and prevention business in Financial Services

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