Data Engineer, Data Integration & Performance Platform (12-Month Contract)
Ontario Municipal Employees Retirement System1 day ago
Toronto, CanadaEntry Level
Responsibilities
- Analyze source and target data to profile records, investigate reconciliation breaks, validate transformations, and support migration activities.
- Build and test data pipelines converting holdings, transactions, and reference data into BlackRock Aladdin.
- Help design and maintain integrations between Aladdin, order management, treasury, private markets, and market data systems.
- Contribute to the Snowflake Integrated Data Platform, including data modelling, data quality controls, lineage, and documentation.
- Own small data capabilities end-to-end with mentorship, including requirements, design, implementation, support models, monitoring, controls, and production delivery.
- Define and execute integration, performance, regression, and business test plans; participate in defect triage and root-cause analysis.
- Document data dictionaries, metadata, lineage, business processes, and knowledge-base articles.
- Collaborate with investment, operations, risk, performance, finance, engineers, architects, vendors, and business analysts.
- Support change adoption through stakeholder-impact analysis, end-user training, and communications.
Requirements
- Bachelor's degree in Computer Science, Engineering, Mathematics, Finance, Accounting, Economics, or a related field, graduating in the current year or within the last 12 months.
- Strong foundational SQL skills, including SELECT statements, joins, aggregations, and basic subqueries.
- Working knowledge of Python, including writing functions, using libraries such as Pandas, and automating basic data tasks.
- Academic coursework or projects involving databases, data modelling, ETL/ELT concepts, cloud computing, data warehouses, or data quality.
- Interest in investment systems, financial markets, or data platforms demonstrated through coursework, internships, personal projects, or extracurricular activities.
- Ability to work through ambiguity, shifting priorities, and reprioritization while raising issues and proposing solutions.
- Exposure to generative AI tools and prompt engineering is expected or encouraged for analysis and documentation.
- Preferred exposure to performance and attribution, order management and trade lifecycle, investment accounting, IBOR/ABOR concepts, or investment platforms.
- Preferred exposure to BlackRock Aladdin, Aladdin Data Cloud, eFront, Charles River, Calypso, Eagle PACE, SimCorp Dimension, FactSet, Bloomberg, or Yardi.
- Preferred exposure to Snowflake, Azure, dbt, Prefect, Azure DevOps, or comparable modern data-stack tooling.
- CBAP, CFA, cloud, Snowflake, Azure, or data-related certifications are assets.
- Clear communication skills and the ability to work with portfolio managers, operations leads, data engineers, and other stakeholders.
Benefits
- 12-month contract with potential extension and conversion to a permanent role.
- Mentorship and code reviews from a senior data engineer.
- Real production ownership and exposure to conversion, integration, platform, and custom data solutions.
- Potential path to a permanent Senior Data Engineer role over time.
- Eligibility for group benefits and retirement plans, subject to applicable offer-letter details.
- Potential eligibility for annual incentive awards under short-term and long-term incentive plans, where applicable.
- Inclusive, barrier-free workplace with employee resource groups, recognition programs, and wellness and development support.
About Ontario Municipal Employees Retirement System
OMERS is a defined benefit pension plan for Ontario municipal employees that administers pensions and invests member and employer contributions across public and private markets globally. Founded in 1962 and headquartered in Toronto, it serves over half a million members from about 1,000 municipal and local-agency employers, with investing platforms spanning infrastructure, private equity, credit, and real estate via Oxford Properties.