Junior Data Engineer (12-month Contract)

SUMMARY 

The Junior Data Engineer is an early-career technical role that supports the development, validation, documentation, and sustainment of trusted data products and analytical foundations used for regulatory decision-making. This role completes assigned tasks across data ingestion, transformation, testing, documentation, reporting support, and operational follow-up. This role is designed for a recent graduate or early-career candidate with relevant education, co-op, internship, project, or portfolio experience who wants to grow on a data engineering career track while contributing to practical analytics, governance, and data product delivery. 

ACCOUNTABILITIES 

• Support the design, development, testing, and maintenance of data pipelines, notebooks, scripts, jobs, and reusable transformation logic under the guidance of senior data engineers and technical leads. 

• Assist with data ingestion and integration from internal systems, external files, APIs, databases, regulated submissions, and enterprise platforms using approved patterns and standards. 

• Write, review, and maintain basic SQL, Python, and related data transformation logic to clean, standardize, join, validate, and prepare data for downstream analytics, reporting, and data products. 

• Create, run, and document data quality checks, reconciliation procedures, regression tests, validation rules, and issue investigations using established methods. 

• Use Git, Azure DevOps, work items, peer review comments, release notes, and approved branching practices to support controlled code changes and deployment readiness. 

• Monitor scheduled jobs, pipeline runs, data refreshes, and operational alerts; investigate common failures, document findings, support root-cause analysis, and escalate risks or unclear issues to senior team members. 

• Prepare and maintain practical engineering documentation, including data dictionaries, technical notes, runbooks, test results, issue logs, decision records, and release support materials. 

• Apply established standards for naming, modular code, reusable templates, data contracts, data quality, metadata, access control, privacy, security, version control, and release discipline. 

• Support metadata and governance-by-design activities by capturing lineage notes, catalogue information, glossary terms, ownership details, classification information, certification status, and access workflow updates as part of delivery. 

• Assist with modernization and migration activities involving legacy and current platforms, including SQL Server, Synapse, Dataverse, SharePoint, Databricks, Fabric, and other enterprise systems. 

• Support analytics, reporting, and self-service enablement as a downstream consumer of engineered data by helping prepare reliable datasets, semantic layer inputs, dashboard support materials, and user-facing documentation when assigned. 

• Participate in cross-functional data modernization initiatives by completing assigned technical, analytical, documentation, coordination, and support tasks with increasing independence over time. 

JOB REQUIREMENTS 

• Recent completion of an undergraduate degree in Computer Science, Software Engineering, Data Science, Information Technology, Management Information Systems, Business Technology Management, Statistics, Business Analytics, Mathematics, or a related technical or analytical discipline. 

• Foundational technical experience gained through co-op placement, internship, academic project, portfolio work, hackathon, certification, volunteer experience, self-directed learning, or equivalent exposure. 

• Basic working knowledge of SQL and at least one programming or scripting language, preferably Python; exposure to R, JavaScript, C#, or similar languages is also relevant. 

• Foundational understanding of relational data, data quality, data transformation, data modelling, APIs, reporting datasets, analytics workflows, or software development practices. 

• Exposure to data platforms, analytics tools, version control, or cloud services such as Databricks, Microsoft Fabric, Power BI, Azure Data Factory, Azure Data Lake, SQL Server, Git, or similar tools is an asset; direct professional experience with every tool is not expected. 

• Strong learning agility, curiosity, and willingness to build depth in data engineering, analytics, data products, metadata, governance, self-service reporting, machine learning, generative AI, and responsible AI use. 

• Strong initiative and follow-through, including the ability to take ownership of assigned tasks, ask clear questions, seek feedback, and move work forward with guidance. 

• Strong attention to detail and ability to maintain clear technical notes, trackers, documentation, test results, and action logs. 

• Strong written and verbal communication skills, including the ability to explain what was done, what was found, what is unclear, and what support or decision is needed. 

• Ability to work collaboratively with technical and non-technical stakeholders in a cross-functional delivery environment. 

• Interest in public-sector or regulatory work, including using trusted data to support fair, timely, explainable, and defensible decisions. 

• Relevant academic projects, portfolio work, certifications, hackathons, co-op terms, internships, volunteer experience, or self-directed learning are considered valuable evidence of readiness. 

EDUCATION 

• Undergraduate degree or diploma in Computer Science, Software Engineering, Data Science, Information Technology, Management Information Systems, Business Technology Management, Statistics, Business Analytics, Mathematics, or a related technical or analytical discipline; recent graduates and early-career candidates with relevant academic, co-op, internship, project, portfolio, certification, or equivalent experience are encouraged to apply.