Data & Analytics Engineer - Synapse BA at Morgan Stanley

Budapest, Central Hungary, Hungary -

Full Time

Start Date

Immediate

Expiry Date

22 Jan, 26

Salary

0.0

Posted On

24 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Management, Data Governance, Data Quality, Data Visualization, Data Analysis, Data Manipulation, Data Lineage, Metadata Management, Data DevOps, PII Management, Finance Regulatory Drivers, Root Cause Analysis, Reporting Services, Self-Serve Dashboards, Collibra, Tableau, PowerBI

Industry

Financial Services

Description

-Be part of a team of innovative data management experts who will engage with business, operational and technology teams in order to: -Inform them and provide guidance on the concepts of data management and governance. -Support their efforts to deliver and maintain the firm's Global Data Quality Policy. -Pursue data quality best practices and implement rules which will mitigate the risks related to the data used in the firm. -Deliver regulatory requirements pertaining to the data used or produced by the firm. -Provide support and guidance on queries related to data cataloguing and extracts -Self-Serve Dashboards, Metrics, Reports support and associating minor/moderate fixes when required -Perform root cause analysis, identifying common themes across data issues and suggest solutions - triaging amongst internal Teams -Understand, capture and document new requirements relating to Reporting Services -Demonstrated experience in enterprise data management, data quality principles and methodologies. -Experience with data visualization technologies (such as Tableau, PowerBI). -Experience with data analysis and manipulation (such as DataIKU, PowerQuery). -Experience with data centric tools around data lineage and dictionaries, common data access APIs, golden source identification, ontology/taxonomy development, Data DevOps. -Experience with meta data management tools (such as Collibra). -Experience with management of PII and other sensitive data. -Understanding of finance regulatory drivers (Mifid II, AML, KYC) Our innovative team delivers deep technical and mathematical expertise to support the Firm's capabilities in quantitative analysis, data analysis, and risk management. LI-RV1 #BPTECH #LI-hybrid 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

The Data & Analytics Engineer will engage with various teams to provide guidance on data management and governance, support the Global Data Quality Policy, and implement best practices for data quality. They will also perform root cause analysis on data issues and document new reporting requirements.