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Data Engineering
Data Engineer
Strong Middle
Bulgaria, Sofia
Hybrid
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Our client is a leading global investment management company headquartered in London. It manages over $228 billion in assets and serves institutional investors, pension funds, wealth managers, and other sophisticated clients worldwide. The firm specializes in quantitative investing, alternative investments, systematic trading strategies, and technology-driven asset management. Data science, machine learning, and AI are core components of its investment and research processes.
As part of our collaboration we will focus on two foundational capabilities required to enable safe and scalable AI adoption across the enterprise: Agentic Security and AI-Ready Data Foundations.
What project we have for you
We build the data foundations that make AI useful and safe inside a regulated financial firm. The value of AI is capped by the data its agents can reach: if an agent cannot find, interpret, trace or be correctly permissioned against data, the capability is useless, or worse, unsafe. Your job is to close that gap.
As part of the Data Management team within Data & Machine Learning at Man Technology (London & Sofia), you will onboard and govern the financial and alternative data that powers our investment teams, and help turn a large data estate into something both people and AI agents can use with confidence. You will build and improve the pipelines, metadata catalogue, security master, identifier mapping, data quality controls and market data permissions that sit underneath it. You’ll be a hands-on Python and SQL engineer who is comfortable working with AI agents, and you’ll work closely with portfolio managers, researchers, data scientists and engineers.
What you will do
- Provide first-level data support to portfolio managers, researchers, traders, engineers and data scientists across the firm.
- Lead the onboarding and integration of a wide range of financial and alternative datasets (reference, ESG, market and alternative data) into the data lakehouse.
- Design and build ETL pipelines using industry-standard and proprietary technologies. Work with engineering teams to define and optimise data models, schemas and workflows.
- Proactively identify and resolve data quality issues before they affect downstream users, and drive data quality management together with engineering.
- Own and enhance security master content and identifier mapping tools, keeping data accurate and consistent across systems.
- Manage market data permissions, improve usage tracking, analyse usage patterns, and optimise cost attribution and charge models.
- Curate and maintain a metadata catalogue and knowledge base, and support data lineage and governance.
- Automate daily tasks wherever possible and help build a scalable data ingestion and management framework, including dashboards and an optimised ongoing data management process.
- Learn the details of the various vendor data sources the firm uses, and act as a subject matter expert on selected projects, providing high-quality data analysis and quality assurance.
- Comply with all company policies on risk, compliance and confidentiality, and escalate risk issues to the appropriate level.
What you need for this
- 3+ years of experience in a data management, data engineering or analyst role
- Strong academic record and a higher education degree with a high mathematical and computing content, such as Computer Science, Mathematics or Engineering.
- 2+ years of experience with data and data wrangling in a finance or finance-related firm.
- Experience with ETL pipelines and data lakehouse concepts
- Programming skills in Python and SQL.
- Strong problem-solving skills.
- Strong analytical skills and strong written and verbal communication skills.
- Self-organised, with the ability to manage time across multiple projects and competing business priorities.
- Familiarity with data from financial data aggregators such as Refinitiv, FactSet, S&P, IHS or Bloomberg.
- Working knowledge of databases, Linux/UNIX, Git and Jira.
- Interest in or exposure to alternative, ESG and market data.
- Commitment to excellence, integrity and personal accountability, including escalating issues when appropriate.
- Client focus: understands internal stakeholders, speaks their language and manages their expectations.
- Original and innovative thinking, with a positive attitude and an interest in continuously building new skills.
- Comfortable in an entrepreneurial environment, and a collaborative, diligent team member.
- Passion for using science, technology and data to improve the investment process.
What it’s like to work at Intellias
At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth.
We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law.
We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.
Skills
Python
SQL
