Senior Data Engineer, Data Integration & Performance Platform (12-Month Contract)
Ontario Municipal Employees Retirement System2 months ago
Toronto, CanadaSenior
Responsibilities
- Design, build, and maintain high-performance ETL and ELT pipelines using incremental loading, change data capture, historisation, and idempotent replay.
- Ingest, transform, and serve data from Aladdin, legacy platforms, vendors, and other source systems into Snowflake.
- Implement bronze, silver, and gold medallion architecture with embedded data quality controls.
- Write production-grade SQL and Python/PySpark code and optimize queries, partitioning, and warehouse sizing.
- Own pipeline orchestration, including scheduling, monitoring, retries, and failure alerts with defined SLIs and SLOs.
- Design relational and dimensional data models supporting investment analytics, performance, accounting, and risk reporting.
- Define source-to-target mappings, version-controlled transformations, data quality controls, dashboards, notifications, and end-to-end lineage.
- Own data capabilities through design, implementation, production deployment, monitoring, support models, and runbooks.
- Engineer data services and APIs that address gaps between Aladdin and investment, risk, performance, and finance requirements.
- Implement Infrastructure-as-Code and CI/CD pipelines for repeatable and auditable data-platform deployments.
- Define and execute unit, integration, performance, and regression tests and participate in defect triage and root-cause analysis.
- Write technical specifications and acceptance criteria, review vendor deliverables, and escalate quality or completeness gaps.
- Support current investment data platforms and validate that required data behavior is preserved during migration.
- Document data dictionaries, lineage diagrams, metadata, and knowledge-base articles.
- Apply change-management practices, including stakeholder-impact capture, end-user training, and communications.
- Operate across Agile and waterfall delivery models while documenting scope, deliverables, and technical timelines.
Requirements
- At least 6 years of experience in data engineering, software engineering, or data-platform roles, including work with investment platforms, order management, investment accounting, data warehouses, or cloud data platforms.
- Senior Data Engineer-level or higher experience working directly with investment systems across at least two of performance measurement and attribution, investment accounting, order management, and risk.
- Expert-level SQL skills, including complex joins, window functions, aggregations, data profiling, and performance investigation.
- Strong relational and dimensional data-modelling experience.
- Production experience with Snowflake or an equivalent cloud data warehouse, including performance tuning, zero-copy cloning, time travel, and role-based access control.
- Strong working knowledge of Python and data-engineering libraries such as PySpark, Pandas, or Polars.
- Deep understanding of ETL and ELT design patterns, incremental loading, change data capture, historisation, data quality, and idempotency.
- Experience with orchestration tools such as Prefect, Airflow, Azure Data Factory, or Dagster.
- Experience building integrations with investment systems and handling JSON, XML, flat files, and APIs.
- Depth in one or more investment data domains, such as security and reference data, positions and transactions, portfolio accounting, order and trade lifecycle data, performance, or risk analytics.
- Working knowledge of investment lifecycles across exchange-traded and OTC products, including derivatives and structured or look-through instruments.
- Strong experience with Git, branching strategies, and CI/CD pipelines for data code using tools such as dbt or Azure DevOps.
- Experience owning a data capability over its lifecycle and designing reusable data products.
- Experience with investment platforms such as BlackRock Aladdin, Aladdin Data Cloud, eFront, Charles River, Calypso, Eagle PACE, SimCorp Dimension, FactSet, Bloomberg, or Yardi is preferred.
- Hands-on experience with dbt, Azure Data Lake, Azure Data Factory, Azure DevOps, advanced Snowflake, and Prefect or equivalent orchestration is preferred.
- Experience with Terraform, ARM, or Bicep for cloud-resource provisioning is preferred.
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.
- Cloud or data-engineering certifications are valued but do not replace demonstrated delivery experience.
- Clear technical communication skills and the ability to work with portfolio managers, operations leads, data architects, business analysts, and engineers.
- Experience using generative AI tools and prompt engineering for analysis, documentation, and code generation is valued.
Benefits
- 12-month contract with salary prorated based on the contract term.
- Eligibility for an annual Incentive Award under the Short-term Incentive plan and, if applicable, the Long-Term Incentive plan.
- Potential participation in group benefits and retirement plans.
- Inclusive, barrier-free recruitment and selection process with employee resource groups, Purpose@Work, and recognition programs.
- AI tools may support certain recruitment stages, while human judgment remains central to decision-making.
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.