Senior Business Analyst

Intellias; Polska; Sur place; PLN 120 000 - 180 000; Plein temps

Résumé du poste

Intellias is seeking a Business Analyst to join a delivery team on a large-scale enterprise data platform migration for a financial services client. You will bridge client domain owners and stewards with delivery engineers, owning the backlog in Azure DevOps and contributing to a federated data model.

You will run data modelling workshops, design conceptual and logical models, ensure traceability to business terms, and collaborate on standards, CI/CD, and automation.

Qualifications

• Substantial data modelling experience powering production data models.
• Credible domain knowledge in asset/investment management.
• Ability to run workshops with business stakeholders.
• Experience with data governance, dictionaries, and glossaries.
• Comfort with versioning models in a repository and code review.

Responsabilités

• Run data modelling workshops with business SMEs and domain owners.
• Design conceptual and logical data models across domains.
• Ensure traceability from business terms to delivered columns.
• Review domain models and contribute to federated data models.
• Define reusable structures and nesting rules to prevent domain conflicts.
• Work in Git/GitHub and manage reviews, PRs, and releases.
• Support automated CI checks and governance standards.

Connaissances

Data modelling

Domain knowledge

Workshop facilitation

Precise communication

Outils

Git & GitHub

YAML

JSON

Schema languages

Description du poste

We are hiring a Business Analyst to join an Intellias delivery team on a large-scale enterprise data platform migration programme for a financial services client. You will bridge the client’s domain owners and stewards on one side and the delivery engineers on the other, and you will own the backlog in Azure DevOps.

What project we have for you

Our client is an independent, active global asset manager with over R3 trillion in assets under management. They are executing a firm-wide data strategy to govern, manage and engineer data as a product across more than 70 business-owned sub-domains.

As part of this, they are migrating to Databricks as the foundational layer of their Enterprise Data Platform, adopting a lakehouse architecture built on open formats, declarative pipelines and Unity Catalog.

What you will do

• Run data modelling workshops with business SMEs, domain owners, analysts.
• Design conceptual and logical data models across multiple business domains, working from business definitions as well as from existing data structures in mastering systems.
• Model business complexity appropriately: e.g. class hierarchies, inheritance, controlled vocabularies, reusable patterns, shared data domains, business rules, and define where cross-domain references exist.
• Present models back to stakeholders for review, information-sharing, and agreement
• Ensure every model element traces back to a business term from data governance, and that the trace survives all the way to the delivered column. Help to resolve conflicts or missing inputs/outputs where they exist
• Review other domain data models from the modelling team. We envisage a small team of modellers who contribute to the federated data model as a whole.

Standards and federation

• Contribute to and enforce the modelling standards that make federated delivery safe: naming conventions, data type standards, model layering rules, and the conventions that prevent domains colliding as the model grows
• Define reusable enterprise-level structures — shared types, reusable/common patterns, balancing core versus domain-local

Delivery and automation

• Work in Git and GitHub as your primary environment: branches, pull requests, code review, releases
• Review model changes raised by others — including, ultimately, any changes drafted by AI agents — and apply the judgement that automated checks cannot
• Version models, assess the impact of breaking changes on downstream consumers in order for migration planning
• Contribute to the automated checks that enforce standards in CI, in collaboration with engineering
• Have input into the logical-to-physical mapping — deciding and documenting where a normalised structure can/should be denormalised for query performance or analytics (e.g. a data product), an define agreed and named patterns for these transformations rather than ad-hoc judgement so they can be automated.

What you need for this

Key Responsibilities

• Substantial data modelling experience, with a track record of conceptual, logical modelling that powered physical models that went into production, consumed, iterated upon & versioned accordingly. You must be competent in the principles of abstraction, inheritance, normalisation. Experience with dimensional/denormalization techniques.
• Demonstrable domain knowledge in asset/investment management, or a closely related financial services area — sufficient to hold a credible conversation with a SME, e.g. a portfolio manager, a fund accountant or a risk analyst about what their data actually means.
• We are building out domain by domain. You would be expected to develop working depth across more than one area. We expect some in depth asset management knowledge in at least 3 of these areas:
• Instrument/Security reference, Index & Benchmarks, Party, Counterparty/ Client, Portfolio, Holdings & Valuations, Execution, Trade Life cycle, Performance & Attribution, ESG/sustainability, Fund Accounting, Sales & Marketing
• Working fluency with Git and GitHub: branching, pull requests, resolving conflicts, reviewing others’ changes. You do not need to be a software engineer, but you must be comfortable that your model lives in a repository and moves through code review.
• Comfort authoring in YAML, and working with JSON data – plus the willingness to learn a schema language – prior exposure is welcome but not expected.
• Experience establishing or working to modelling standards — naming conventions, data dictionaries, glossaries, and the ability to add/enhance those standards as part of the platform maturation and greater automation.
• Soft Skills: The ability to run a workshop with business stakeholders and leave with clarity, and not a list of open questions. Precision with language. Dealing with ambiguity. Much of this role is writing definitions that all stakeholders can agree on.

Nice to have:

• Databricks, Delta Lake or a comparable Lakehouse platform
• Data contracts, particularly ODCS, or equivalent interface-versioning practice
• CI/CD concepts
• Experience of developing/using agentic workflows for delivering model artefacts
• Experience of a federated or data mesh operating model, and its failure modes
• Traditional modelling tools such as Erwin, ER/Studio is useful, for reference, however our way of working will be different.

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.