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

Role Overview

Delivery Areas

• Assist with data pipelines that convert holdings, transactions, and reference data into Aladdin and resolve reconciliation breaks through parallel runs.
• Help maintain integrations across order management, treasury, private markets, and market data providers.
• Contribute to Snowflake data modelling, data quality controls, and lineage using an integrated data platform.
• Support custom capabilities for investment, risk, performance, and finance teams.

Analysis and Requirements

• Interpret business requirements, user stories, acceptance criteria, process models, data-flow diagrams, and source-to-target mappings with senior engineers and business analysts.
• Query source and target systems to profile data, investigate breaks, validate transformations, and prove implementation correctness.
• Participate in design sessions with investment, operations, risk, performance, and finance stakeholders.

Capability Ownership

• Own a small data capability end to end with mentorship, from problem definition and solution shaping through production and operational accountability.
• Design reusable capabilities instead of one-off point solutions.
• Define support models, monitoring, controls, and documentation so delivered capabilities can be operated by an operations team.

Testing and Quality

• Define and execute integration, performance, regression, and business test plans.
• Participate in defect triage, root-cause analysis, and resolution across environments.
• Write requirements and acceptance criteria and review systems integrator deliverables against them.
• Work across Agile and waterfall delivery models while documenting scope, deliverables, and timelines.

Current and Target State

• Build knowledge of current investment data platforms, processes, calculations, and downstream consumers to define target-state migration needs.
• Investigate current-state data issues, trace lineage, and validate that behavior is preserved through migration.
• Build and maintain data dictionaries, lineage, metadata, and knowledge-base articles.

Change and Adoption

• Apply change management principles, capture stakeholder impacts, support end-user training, and communicate changes to encourage adoption.

Required Qualifications

• Bachelor's degree in a relevant field, graduating in the current year or within the last 12 months.
• Strong working knowledge of SQL and working knowledge of Python, including basic data automation.
• Academic exposure to databases, data modelling, ETL or ELT, cloud computing, data warehouses, and data quality.
• Interest in investment systems, financial markets, or data platforms.
• Comfort with ambiguity, shifting priorities, and taking initiative.

Preferred Qualifications

• Evidence of owning a project or data capability through its lifecycle.
• Exposure to investment domains, investment platforms, or modern data-stack tools such as Snowflake, Azure, dbt, Prefect, or Azure DevOps.
• CBAP, CFA, cloud, or data-related certification is an asset.
• Generative AI tools and prompt engineering experience or interest are valued for analysis and documentation.

Compensation

• The expected salary range is $72,000 to $108,000 per year, prorated for the contract term.
• The role may also be eligible for incentive awards and group benefits and retirement plans.