Data Engineer, Analyst at BlackRock

Budapest, Central Hungary, Hungary -

Full Time

Start Date

Immediate

Expiry Date

11 Feb, 26

Salary

0.0

Posted On

13 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, Data Pipelines, ETL, ELT, Unix, Scripting, Data Processing, Data Quality, Financial Data, Cloud Technologies, Machine Learning, Data Integration, Version Control, Automation

Industry

Financial Services

Description

About this role Our Data Engineering team provides the data and platform for the Researcher and Application Engineering teams and the users of applications. Our responsibility is to ensure the operation of our data platform, availability and freshness of data, extending the scope with new subject areas, supervise and improve the accessibility of data. We foster a work environment where we enjoy freedom to contribute ideas, make decisions and express diverse viewpoints. Our Budapest center and our global data team are growing, presenting new opportunities. Your role and impact You will focus on improving the experience of our internal and external clients working with our data. You will have chance to influence the future roadmap of our environment, evaluating emerging technologies and integrating them improving data governance. You will work closely with business teams to understand their data needs and make additional data sources available for them. You will also work with Unix, Database and Access administration and Application teams to support daily operations, manage data access performance and ensure data quality. Your responsibilities Understand, secure, improve existing and create new ETL & ELT data pipelines Understand and tackle challenges regarding acquiring, processing and accessing distributed data sets Support end users and application developers to find relevant data for their needs and provide them with the optimal way accessing it Implement scripts to automate data operations and measure data quality Pro-actively seek and resolve data anomalies Answer questions about financial data content You should be Self motivated, with a hands-on personality and talent to understand the underlying business processes of an application and can work on resolutions with the technical team. Curious about your profession. Keen to learn and keep up to date. You have: Practical experience building processes using advanced SQL, Python, Data Pipelines, ETL/ELT At minimum user level experience with Unix/Linux, scripting knowledge a plus Exposure to workload automation and distributed data processing principles Strong analytical skills and tenacity for digging into complex processes Enjoy working with financial data and collaborating within a team setting Exposure to cloud technologies, machine learning, object oriented design, data integration and lineage tools, continuous integration, version control, and releases would be a plus. Useful skills BSc or MSc in Economics, Computer Science or equivalent experience Proven ability to code and automate production quality data pipelines Experience within financial sector or strong interest in learning financial markets Our benefits To help you stay energized, engaged and inspired, we offer a wide range of employee benefits including: retirement investment and tools designed to help you in building a sound financial future; access to education reimbursement; comprehensive resources to support your physical health and emotional well-being; family support programs; and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about. Our hybrid work model BlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person – aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock. About BlackRock At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being. Our clients, and the people they serve, are saving for retirement, paying for their children’s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress. This mission would not be possible without our smartest investment – the one we make in our employees. It’s why we’re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive. For additional information on BlackRock, please visit @blackrock | Twitter: @blackrock | : BlackRock is proud to be an Equal Opportunity Employer. We evaluate qualified applicants without regard to age, disability, race, religion, sex, sexual orientation and other protected characteristics at law. BlackRock's purpose is to help more and more people experience financial well-being. As a global investment manager and a leading provider of financial technology, our clients—from grandparents, doctors, and teachers to large institutions—turn to us for the solutions they need when planning for their most important goals. People join our firm from around the world to gain real-world experience while making an impact. Discover how you can have a career at BlackRock that's exciting, rewarding and full of possibilities.

Responsibilities

You will focus on improving the experience of internal and external clients working with data, ensuring data quality and accessibility. Your role includes creating and managing ETL & ELT data pipelines and supporting end users in finding relevant data.