Senior SQL Server & Data/AI Engineer
Mitsubishi Heavy Industries, Ltd.
Job Description
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Job Title
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Senior SQL Server & Data/AI Engineer
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Department
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IT/ERP
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Reports to
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Director
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Job Category
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Yearly
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Job Description
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About MHI Canada Aerospace, Inc.
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MHI Canada Aerospace, Inc. (MHICA), a group company of Mitsubishi Heavy Industries, is a Tier 1 manufacturer of major aircraft structures and assemblies, based in Mississauga, Ontario. Over the past decade, MHICA has built more than aircraft components, it has built a recognized worldwide reputation for capacity, precision, on-time delivery, and excellence. MHICA has two state-of-the-art facilities combined to 476,000 sq. ft. This comprises of Manufacturing & Assembly, Engineering, Quality and Supply Chain, where highly-skilled employees are working on Bombardier's sector-leading Global 5000/6000 and Challenger 350 business aircraft. MHICA's technicians build and join wing assemblies and fuselage sections, as well as perform systems and flight control assembly installations and testing.
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Scope of Position
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Reporting to the Director, the Senior SQL Server & Data/AI Engineer will own our SQL Server data layer end-to-end and help lay the foundations for our AI platform. Roughly 70% of your time will be on SQL Server, ETL, and data modelling: stabilizing, tuning, and improving what we already run in production. The rest will be spent designing data structures and pipelines for AI (vector store, RAG-style data access) and, if it makes sense, basic semantic models/SSAS.
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Infrastructure/IT will manage servers, OS, and patching. You own schema, code, performance, ETL, and data models. You’ll be expected to make architecture decisions, challenge assumptions, and push for robust, maintainable solutions.
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Responsibilities
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SQL Server Ownership (Data Layer)
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- \n Own several production SQL Server instances and ~10 databases from a data perspective (schemas, code, performance, reliability, security at the DB level, backups/restore strategies).
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- \n Monitor and tune performance:
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- \n Index and statistics strategy, query plans, blocking/deadlocks, resource usage.
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- \n Maintain and troubleshoot:
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- \n Replication, SQL Agent jobs, and other DB-level automation.
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- \n Design and implement:
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- \n Tables, views, indexes, constraints, and other DB objects for new features and integrations.
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- \n Work with infrastructure/IT on:
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- \n Capacity, patching windows, and DR, while ensuring the data layer supports those plans.
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ETL & Data Workflows
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- \n Own and improve existing ETL workflows (SSIS packages and/or custom ETL processes).
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- \n Stabilize ETL:
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- \n Add proper logging, monitoring/alerting, and restart/recovery patterns.
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- \n Document and rationalize data flows:
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- \n Between SQL databases, ETL, upstream applications, and reporting/analytics.
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- \n Improve data quality:
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- \n Implement validation checks, reconcile source vs target, and create repeatable fixes for recurring data issues.
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SQL Development & Optimization
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- \n Refactor and optimize stored procedures, functions, and queries to reduce runtime, resource usage, and complexity.
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- \n Debug and resolve production data issues:
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- \n Do real root-cause analysis (schema, ETL logic, upstream systems) rather than just patch symptoms.
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- \n Establish and enforce SQL development standards:
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- \n Naming conventions, error handling, transaction handling, deployment/version control for DB objects.
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AI & Data Platform Enablement (Cloud-Friendly)
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- \n Prepare and structure enterprise data for AI use cases (RAG, copilots, internal assistants, automation).
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- \n Design and implement a vector-aware data store using pragmatic options (e.g., Azure SQL, managed vector stores, or similar), including:
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- \n Schemas for documents, embeddings, and metadata.
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- \n Ingestion and refresh pipelines that keep AI-ready data up to date and governed.
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- \n Work with AI developers and stakeholders to define:
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- \n What data AI can access, under which rules, and via which APIs/queries.
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- \n Help evaluate:
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- \n When to use Azure or other cloud services (e.g., Azure OpenAI, managed search/vector services) and how they integrate with on-prem SQL.
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Collaboration & (Light) Analytics Enablement
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- \n Partner with application developers, BI/reporting, and business stakeholders to ensure data structures match actual usage.
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- \n Translate business questions into reusable models/views/semantic layers where possible.
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- \n If relevant and time allows, explore:
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- \n Basic SSAS/semantic models or equivalent for stable reporting and as a source for AI tools.
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Work Conditions
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- \n Overtime hours with advanced notice may be required to meet project deadlines.
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- \n Hybrid opportunities available – incumbent must commute to work.
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Skills and Qualifications
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- \n 5+ years hands-on experience as a SQL Server Developer / Database Engineer / Data Engineer with SQL Server as your main platform.
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- \n Strong T-SQL skills:
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- \n Complex stored procedures, functions, and views.
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- \n Solid query tuning using execution plans, index strategies, and statistics.
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- \n Proven ETL / data integration experience:
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- \n Designing, owning, and troubleshooting production ETL jobs (SSIS or similar tools, or custom script-based ETL).
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- \n Solid grasp of:
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- \n Relational data modelling, normalization vs denormalization, and the impact of design on performance and maintainability.
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- \n Comfortable taking over legacy SQL and ETL:
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- \n Reading messy code, simplifying it, and documenting what’s actually happening.
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- \n Used to owning outcomes:
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- \n You can prioritize, communicate trade-offs, and defend good technical decisions to both technical and non-technical stakeholders.
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- \n Clear written and verbal communication.
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Nice to Have
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- \n Experience with LLM/AI systems:
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- \n RAG-style architectures, embeddings, prompt design, chatbots, or internal copilots.
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- \n Hands-on exposure to vector databases / vector stores or search platforms with vector capabilities (cloud or self-hosted).
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- \n Experience with:
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- \n SSIS, SSRS, SSAS, or similar ETL/reporting/analytics tools.
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- \n Power BI modelling (DAX is a plus but not mandatory).
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- \n Programming in .NET/C# or Python for data/ETL/AI integration and automation.
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- \n Background in manufacturing, aerospace, or industrial environments with data flowing between ERP, PLM, MES, and quality systems.
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Education
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- \n A college diploma or university degree in computer science or software engineering.
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Please note – the Company will conduct a criminal background check upon hire.
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We thank all applicants in advance for their interest; however, only those candidates selected for an interview will be contacted.
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MHI Canada Aerospace is an equal opportunity employer and encourages women, aboriginal people, persons with disabilities and members of visible minorities to apply. MHICA is committed to providing employment accommodation in accordance with the Ontario Human Rights Code and the Accessibility for Ontarians with Disabilities Act, 2005 (AODA). MHICA will provide accommodations to job applicants with disabilities throughout the recruitment process. If you require an accommodation, please notify us and we will work with you to meet your needs.
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