Business Analyst, Data Integration & Performance Platform (12-Month Contract)

OMERS•Toronto, ON

2d•CA$86,000 - CA$130,000•Remote

About The Position

This is an early-career role on a multi-year investment platform transformation that is replacing our core investment book of record with BlackRock Aladdin and building a new cloud data platform on Snowflake. We are hiring deliberately at the Business Analyst level. You do not need an extensive resume to contribute here. You need a growth mindset, genuine intellectual curiosity, and the willingness to build your skills inside a fast-moving delivery environment. You will sit inside the Data Platform and Integration group and support work across four delivery areas, working alongside senior business analysts, engineers and architects. The program is fast moving and priorities shift, so you should expect to move between these areas as the work demands: Conversion. Conversion of holdings, transactions and reference data from legacy platforms into Aladdin, including reconciliation and break resolution through parallel run. Data Integration. System and vendor integrations into and out of Aladdin across order management, treasury, private markets and market data providers. Data Platform. Build-out of our Snowflake based Integrated Data Platform using a medallion pattern, including data modelling, data quality controls and lineage. Custom Solutions. Design of capabilities that close gaps between Aladdin native functionality and what our investment, risk, performance and finance teams require. This team also operates the current production investment data platforms, spanning performance, accounting, order management and integration. You will spend meaningful time in that environment, because the fastest way to become useful on the target state is to understand what today's platforms actually do, which business processes depend on them, and which behaviours must be preserved through the transition. That current-state work is a deliberate part of the role, not a distraction from it. Joining now means working inside a live, complex technology change from the beginning. Navigating evolving requirements, cross-functional stakeholders and real delivery pressure early in a career builds instincts and adaptability that take others years to develop. The capital markets domain knowledge you build here travels well across the financial services industry, and for the right candidate this contract carries a genuine performance-based path to a full-time role. This team is also embedding AI into how we work now, not as a pilot or a future initiative. We expect every member of the team to engage with it seriously, and this role will have a hand in identifying where AI can be embedded within our processes or used to redesign them.

Requirements

0 to 3 years in a business analysis, data or technology-adjacent role. Relevant internships, co-op terms and academic project work are considered.
Working knowledge of SQ/Python and relational databases. You do not need to be an expert, but you should be comfortable writing queries and learning from data. This will be assessed at a level appropriate to the role.
A foundational understanding of requirements gathering, process documentation or user stories, with a clear willingness to deepen these skills on the job.
Active use of AI tools such as Microsoft Copilot, ChatGPT, Claude or similar in your own work. We treat practical AI fluency as a professional skill, and we will ask you how you use these tools today.
Strong written and verbal communication skills, with the ability to convey technical concepts clearly to non-technical audiences.
Analytical and structured in your thinking, comfortable with ambiguity and shifting priorities, and willing to ask questions early rather than wait to be told what to do.

Nice To Haves

Exposure to ETL or ELT concepts, data warehousing fundamentals or data integration patterns, whether through coursework, personal projects or professional experience.
Some awareness of any of the following: performance measurement, investment accounting, order management, or risk. Genuine curiosity about the capital markets domain matters more than existing depth at this level.
Hands-on exposure to investment applications such as Aladdin, eFront, Charles River, Eagle, SimCorp, FactSet or Bloomberg is a plus but not expected.
Familiarity with Snowflake, Azure, dbt, Power BI or comparable tooling is a nice to have.
Bachelor's degree in related fields such as Computer Science, Engineering, Mathematics, Finance, Accounting or Economics.
Progress toward CFA or CBAP certification is an asset but is not a substitute for curiosity and drive.
A track record, however early, of contributing positively to team environments and building relationships across technical and business partners.

Responsibilities

Support requirements gathering and documentation for projects across the four delivery areas, contributing to user stories and acceptance criteria, business requirements documents, process flow diagrams and source to target mapping, and building toward independent ownership of smaller initiatives.
Perform hands-on data analysis with support from senior team members. You will query source and target systems to profile data, investigate discrepancies and validate that what was built is correct, with growing independence over time.
Participate in design sessions and workshops with investment, operations, risk, performance and finance stakeholders, and learn to translate between business intent and technical design.
Support the definition and execution of business test plans, including functional, integration and regression testing, and develop the ability to design and run structured test cases independently.
Participate in defect triage and root cause analysis across environments, and learn how systems integrator deliverables are reviewed against requirements and acceptance criteria.
Work across both Agile and waterfall delivery models, and keep your scope, deliverables and timelines clearly documented and communicated.
Develop a working understanding of the current investment data and platform environment, including the processes, calculations and downstream consumers it supports.
Support the current environment where doing so builds transition knowledge, including investigating data issues, tracing lineage through existing systems and supporting production data quality monitoring.
Contribute to data documentation including data dictionaries, lineage, metadata and knowledge base articles. Institutional knowledge that lives only in one person's head is treated as a defect, and producing clear, structured, discoverable documentation is a skill we expect you to build early.
Actively use AI tools as part of day-to-day analysis and documentation work, and contribute to the team's ongoing effort to identify where AI can be embedded within existing processes or used to redesign them where it adds genuine value.
Contribute to change management activities including identifying stakeholder impacts, supporting end user training and assisting with communications, so that what the team delivers is actually adopted.