Data Engineer Associate at Morgan Stanley

Budapest, Central Hungary, Hungary -

Full Time

Start Date

Immediate

Expiry Date

09 Feb, 26

Salary

0.0

Posted On

11 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Apache Spark, Snowflake, No SQL, Graph Database, dbt, Python, ETL, Web Services, Restful Services, Airflow, Dagster, SQL, Data Modelling, Data Quality, Git, CI/CD

Industry

Financial Services

Description

We are seeking a skilled Data Engineer with hands-on experience in Apache Spark or Similar, Snowflake, No SQL , graph database and dbt to join our growing data team. You will be responsible for building scalable data pipelines, transforming data for analytics and reporting, and ensuring high data quality across the organization. This role is ideal for someone who thrives in a fast-paced environment and is passionate about delivering high-impact data solutions. Proficient in languages like Python, used for scripting, ETL processes, and data manipulation and optimizations. Acquainted with implementing and consuming webservices and restful services. Skilled in Apache Spark (especially PySpark) or equivalent. Hands-on experience with Snowflake, including schema design, data loading, performance tuning, warehouse optimization, and access control. Experience with workflow orchestration tools like Airflow, Dagster, or similar. Solid understanding and hands-on experience with dbt for data transformation and modelling. Strong SQL skills and knowledge of data modelling techniques (star/snowflake schema, normalization). Monitor data pipeline health, ensure data quality, and troubleshoot data issues. Familiarity with Git, CI/CD, and version control best practices. Excellent problem-solving, communication, and collaboration skills. Familiarity with data governance, metadata management, or data catalog tools is added advantage. At least 2 years' relevant experience would generally be expected to find the skills required for this role 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. 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. 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? Speak to our recruitment team to find out more. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential. Our skilled and creative workforce is comprised of individuals drawn from a broad cross section of the global communities in which we operate and who reflect a variety of backgrounds, talents, perspectives, and experiences. Our strong commitment to a culture of inclusion is evident through our constant focus on recruiting, developing, and advancing individuals based on their skills and talents.

Responsibilities

You will be responsible for building scalable data pipelines, transforming data for analytics and reporting, and ensuring high data quality across the organization. Monitor data pipeline health, ensure data quality, and troubleshoot data issues.