Back-end Engineer - Data Platforms
Morgan Stanley1 day ago
Base Salary
$155k - $215k/yr
Responsibilities
- Design, develop, and maintain scalable backend applications, services, APIs, reusable frameworks, and platform capabilities.
- Build distributed data processing solutions, big data frameworks, and real-time and batch processing architectures.
- Design and implement data pipelines for ingestion, transformation, validation, and consumption using Snowflake and cloud-based data platforms.
- Optimize large-scale processing workloads for performance, reliability, and cost efficiency while supporting governance, lineage, observability, and data quality.
- Lead system architecture discussions, technical roadmaps, architecture documentation, design reviews, and code reviews.
- Design graph-based data models and analytics solutions for relationship and network-based insights.
- Establish engineering practices for testing, delivery, performance tuning, operational excellence, automation, and maintainability.
- Mentor junior engineers, provide technical leadership, and promote AI-assisted development tools and workflows.
Requirements
- Bachelor’s or master’s degree in computer science, engineering, information technology, or a related field.
- At least 8 years of software engineering experience with a strong backend development focus.
- Expert-level Python programming experience.
- Strong hands-on experience with PySpark and distributed data processing.
- Experience with big data technologies such as Spark, Hadoop, Kafka, Databricks, and Delta Lake.
- Strong expertise in Snowflake architecture, data modeling, and performance optimization.
- Experience designing and implementing large-scale data pipelines and data platforms.
- Experience with graph technologies and graph-based data solutions.
- Strong understanding of system architecture, application design patterns, microservices architecture, event-driven architectures, distributed systems, and API design.
- Proven experience conducting architecture and code reviews and understanding CI/CD, DevOps, testing frameworks, and software delivery practices.
- Experience using modern AI developer tools and AI-assisted engineering practices.
- Preferred experience includes financial services, risk, AML, transaction monitoring, regulatory technology, data platforms, AWS, Azure, GCP, Docker, Kubernetes, data products, machine learning or AI workloads, data governance, metadata management, and data lineage frameworks.
Benefits
- Morgan Stanley offers comprehensive employee benefits and perks and supports employees and their families throughout their work-life journey.
- The company provides opportunities for career mobility across the business.
- The role offers a base pay range of $155,000 to $215,000 per year, with potential additional incentive compensation and benefits described separately.
Tech Stack
Apache HadoopApache KafkaApache SparkAWSAzureDatabricksDockerGoogle Cloud PlatformKubernetesPythonSnowflake
Categories
BackendData Engineering
About Morgan Stanley
Morgan Stanley is a global financial services firm that provides investment banking, sales and trading, wealth management, and investment management to corporations, governments, institutions, and individuals. It earns fees, commissions, and interest and trading income across advisory, underwriting, brokerage, and asset management businesses. Founded in 1935 and headquartered in New York, the public company operates in more than 40 countries through thousands of offices, including a large U.S. wealth management franchise.