We are looking for a Data Engineer (3-5 years) with strong Python programming skills and hands-on experience building modern data platforms using Snowflake, dbt, and Apache Airflow. You will design and develop reliable data pipelines, model and transform data for analytics, and collaborate using Git-based workflows to deliver high-quality, production-ready data solutions. Experience with Power BI and exposure to AI/ML use cases is a plus.

Key Responsibilities:

Design, build, and maintain scalable ETL/ELT pipelines using Apache Airflow (DAG design, scheduling, monitoring, retries, alerting).
Develop and optimize cloud data warehousing solutions on Snowflake (schemas, performance tuning, clustering/partitioning strategies where applicable, cost awareness).
Implement analytics engineering best practices using dbt:
Data modeling (star/snowflake schemas, dimensional modeling)
Reusable macros, tests, documentation, and lineage
Environment management (dev/test/prod)
Write clean, efficient, and maintainable Python code for data ingestion, transformation, orchestration, and automation tasks.
Ensure data quality and reliability through validation, automated testing, and observability/monitoring.
Use Git-based workflows (branching, PRs, code reviews) and contribute to CI/CD practices for data pipelines and dbt projects.
Troubleshoot pipeline failures, resolve data issues, and continuously improve performance and stability.

Required Qualifications:

3-5 years of professional experience in Data Engineering or related roles.
Hands-on experience with Snowflake, dbt, and Apache Airflow in production or enterprise environments.
Strong programming skills in Python (data processing, APIs, automation, packaging, best practices).
Solid understanding of data engineering concepts:
ETL/ELT patterns, orchestration, batch processing (and streaming familiarity is a plus)
Data modeling, warehousing concepts, and SQL optimization
Strong SQL skills and experience working with large datasets.
Working knowledge of Git-based development workflows (feature branches, pull requests, reviews, merging strategies).

Good to Have (Preferred Skills)
Experience building dashboards or semantic models with Power BI.
Exposure to AI/ML concepts or enabling AI use cases (feature datasets, data prep for model training/inference, LLM/AI pipeline awareness).
Kafka (integration / streaming support)
Great Expectations (data quality checks / validation framework)

Soft Skills:

Strong problem-solving and debugging abilities.
Good communication skills and ability to work cross-functionally.
Ownership mindset with attention to data quality, reliability, and documentation.

WHAT YOU CAN EXPECT FROM MORGAN STANLEY:

At 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.

To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser.

Morgan 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.

Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.

For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.