{"id":1285195,"url":"https://alion.io/job/morgan-stanley-back-end-engineer-data-platforms","title":"Back-end Engineer - Data Platforms","company":{"id":40230,"name":"Morgan Stanley","domain":"morganstanley.com","url":"https://alion.io/company/morgan-stanley","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"B","score":75,"open_postings":78,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":31,"computed_at":"2026-09-28T05:45:00Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":155000,"max":215000,"currency":"USD","period":"year","gross":null,"usd_annual":215000},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Hadoop","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"Kubernetes","optional":true},{"name":"Machine Learning","optional":true}],"status":"live","first_seen_at":"2026-09-09T00:00:00Z","employer_posted_date":"2026-09-22","last_verified_at":"2026-09-28T22:42:56Z","board_verified":true,"closed_at":null,"days_open":19,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":19},"description":"In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Back-end Engineer - Data Platforms position at the Vice President level, which is part of the job family responsible for developing and maintaining software solutions that support business needs.\nMorgan Stanley is an industry leader in financial services, known for mobilizing capital to help governments, corporations, institutions, and individuals around the world achieve their financial goals.\nInterested in joining a team that’s eager to create, innovate and make an impact on the world? Read on.\nWe are seeking a highly skilled Vice President Backend Software Developer to design, build, and scale enterprise-grade data platforms and backend services supporting critical business and regulatory workloads. The ideal candidate combines deep technical expertise in distributed data processing, modern data architecture, and system design with strong engineering leadership, code quality, and AI-enabled development practices.\nAs a VP Backend Software Developer, you will be responsible for architecting and delivering scalable backend systems, data pipelines, and platform capabilities that process large volumes of structured and unstructured data. You will partner with product owners, architects, data engineers, and business stakeholders to build resilient, high-performance solutions while establishing engineering best practices across the development lifecycle.\nThis role requires strong expertise in Python, PySpark, Big Data technologies, Snowflake, Graph Technologies, System Architecture, and AI-assisted software development.\nWhat you’ll do in the role:\nSoftware Engineering & Development\nDesign, develop, and maintain scalable backend applications and services.\nBuild high-performance distributed data processing solutions and big data frameworks.\nDevelop reusable frameworks, APIs, and platform services supporting enterprise applications.\nDrive design and implementation of real-time and batch processing architectures.\nData Engineering & Platform Development\nDesign and implement robust data pipelines for ingestion, transformation, validation, and consumption.\nDevelop scalable solutions by leveraging Snowflake and modern cloud-based data platforms.\nOptimize large-scale data processing workloads for performance, reliability, and cost efficiency.\nSupport data governance, lineage, observability, and data quality initiatives.\nArchitecture & Design\nLead system architecture discussions and define long-term technical roadmaps.\nProduce high-quality architecture and design documentation.\nEvaluate technologies, patterns, and frameworks to improve platform capabilities.\nEnsure solutions meet security, resiliency, scalability, and regulatory requirements.\nGraph & Advanced Data Technologies\nDesign and implement graph-based data models and analytics solutions.\nBuild relationships and network-based insights using graph technologies.\nEvaluate graph databases and related technologies to solve complex business problems.\nEngineering Excellence\nConduct design reviews and code reviews to ensure adherence to engineering standards.\nEstablish best practices for testing, CI/CD, performance tuning, and operational excellence.\nPromote software craftsmanship, maintainability, and automation across teams.\nMentor junior engineers and provide technical leadership.\nAI-Enabled Development\nLeverage AI-assisted development tools to improve engineering productivity and code quality.\nDrive adoption of AI-powered coding, documentation, testing, and review capabilities.\nIdentify opportunities to integrate AI and automation into engineering workflows.\nWhat you’ll bring to the role:\nBachelor’s or master’s degree in computer science, Engineering, Information Technology, or related field.\n8+ years of software engineering experience with a strong focus on backend development.\nExpert-level programming experience using Python.\nStrong hands-on experience with PySpark and distributed data processing.\nExperience with Big Data technologies (e.g., Spark, Hadoop ecosystem, Kafka, Databricks, Delta Lake).\nStrong expertise in Snowflake architecture, data modeling, and performance optimization.\nExperience designing and implementing large-scale data pipelines and data platforms.\nExperience with Graph Technologies and graph-based data solutions.\nStrong understanding of: System Architecture, Application Design Patterns, Microservices Architecture, Event-Driven Architectures, Distributed Systems, API Design.\nProven experience conducting architecture and code reviews.\nStrong understanding of CI/CD, DevOps, testing frameworks, and software delivery best practices.\nExperience using modern AI developer tools and AI-assisted engineering practices.\nPreferred Qualifications\nExperience within Financial Services, Risk, AML, Transaction Monitoring, Regulatory Technology, or Data Platforms.\nExperience with cloud platforms such as AWS, Azure, or GCP.\nFamiliarity with containerization technologies (Docker, Kubernetes).\nExperience building data products supporting advanced analytics, machine learning, or AI workloads.\nKnowledge of data governance, metadata management, and data lineage frameworks.\nWHAT YOU CAN EXPECT FROM MORGAN STANLEY:\nAt Morgan Stanley, we raise, manage and allocate capital for our clients - helping them reach their goals. We do it in a way that’s differentiated - and we’ve done that for 90 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren’t just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you’ll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There’s also ample opportunity to move about the business for those who show passion and grit in their work.\nTo learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser.\nExpected base pay rates for the role will be between $155,000 and $215,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.\nMorgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.\nOur workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.\nFor more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.","description_format":"text","description_chars":7632,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Wealth Management & Financial Advisors","Asset Management & Funds","Investment Banking & M&A Advisory","Online Brokerage & Trading Platforms"],"lifecycle":[{"event":"open","at":"2026-09-26T04:28:36Z"}],"liveness":{"score":49,"band":"ok","label":"Likely open","p_open":1,"p_active":0.547,"p_room":0.9,"age_days":19,"expected_fill_days":31,"reasons":["conf:5","stale_co","velocity","win:mid","comp:brand"],"computed_at":"2026-09-28T05:45:00Z"},"pay":{"stated_usd_annual":215000,"is_top_pay":true},"html_url":"https://alion.io/job/morgan-stanley-back-end-engineer-data-platforms","json_url":"https://alion.io/job/morgan-stanley-back-end-engineer-data-platforms.json","meta":{"generated_at":"2026-09-28T23:22:34Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":987,"day_limit":5000,"remaining_today":4013,"minute_limit":60,"resets_at":"2026-09-29T00:00:00Z"}}}