At a Glance
- Tasks: Build and maintain data infrastructure for cutting-edge AI platforms.
- Company: Join Morgan Stanley, a global leader in financial services with a commitment to innovation.
- Benefits: Enjoy flexible working, competitive salary, and comprehensive employee perks.
- Other info: Collaborative environment with opportunities for career growth and knowledge sharing.
- Why this job: Make a real impact by optimising data processes and driving business insights.
- Qualifications: Experience in data engineering, Snowflake, and strong programming skills in Python.
The predicted salary is between 63000 - 77000 £ per year.
We are seeking a Data Engineering Specialist to join the Architecture & Modernization team.
You will be instrumental in building and maintaining the data infrastructure for our Data AI platforms.
This role will involve hands‑on development, data pipeline creation, and close collaboration with stakeholders across the organization.
This role requires a self‑starter with strong execution skills and the ability to work independently.
You will be expected to not only execute on the current strategy but also contribute to its evolution.
We value diversity of thought and are committed to building a team that reflects the diversity of our global community.
Our mission is to develop a firmwide Artificial Intelligence (AI) Development Platform that aligns with the firm's Technology principles and drives efficiency and consistency, controls, security and strong governance and promotes innovation, enabling teams to build applications that leverage AI capabilities and accelerate the adoption of AI across our businesses.
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 Data & Analytics Engineering position at Director level, which is part of the job family responsible for providing specialist data analysis and expertise that drive decision‑making and business insights as well as crafting data pipelines, implementing data models, and optimizing data processes for improved data accuracy and accessibility, including applying machine learning and AI‑based techniques.
Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.
What you'll do in the role
- Develop and maintain data pipelines and ETL (Extract, Transform, Load) processes.
- Work with structured and unstructured data to ensure it is accessible and usable.
- Optimize data systems for performance and scalability.
- Implement data quality and data governance standards.
- Collaborate with stakeholders across technology and business units to understand their data needs and translate them into technical solutions and provide data‑driven insights.
- Contribute to the documentation and knowledge sharing within the team, creating, and maintaining technical documentation and training materials.
- Participate in code reviews and contribute to the improvement of development processes.
- Contribute to the broader data architecture community through knowledge sharing, presentations.
What you'll bring to the role
- Data Engineering experience with Snowflake and Databricks native solutions.
- Experience on Snowflake Cortex is must.
- Proficiency in programming skills in Python.
- Experience with data processing frameworks like Apache Spark or Hadoop.
- Knowledge of database systems (SQL and No SQL).
- Familiarity with cloud platforms (AWS, Azure) and their data services.
- Understanding of data modeling and data architecture principles.
- Experience with data warehousing concepts and technologies.
- Experience with message queues and streaming platforms (e. g., Kafka).
- Experience with version control systems (e. g., Git).
- Experience using Jupyter notebooks for data exploration, analysis, and visualization.
- Excellent communication and collaboration skills.
- Ability to work independently and as part of a geographically distributed team.
- 8 years+ of being a practitioner in data engineering or a related field would generally be expected to find the skills required for this role.
- #GLTECH#LI-LM1#HYBRID
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.
- Certified
- Persons
- Regulatory
Requirements:
If this role is deemed a Certified role and may require the role holder to hold mandatory regulatory qualifications or the minimum qualifications to meet internal company benchmarks.
Flexible work statement
Interested in flexible working opportunities?
Morgan Stanley empowers employees to have greater freedom of choice through flexible working arrangements.
Speak to our recruitment team to find out more.
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.
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Data Engineering Specialist (Snowflake) in Glasgow employer: PowerToFly
At PowerToFly, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation in the surgical equipment sector. Our Camberley location provides a vibrant environment with ample opportunities for professional growth, supported by comprehensive training and development programmes. We value our employees' contributions and offer competitive benefits, making us a rewarding place to build a meaningful career.
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