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Data Integrations Engineer
Job Location:
Monthly Salary:
Posted:
1 October 2026 (17 days ago)
Posted:
Application Deadline:
29 December 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Tekfortune is a fast-growing consulting firm specialized in permanent contract & project-based staffing services for worlds leading organizations in a broad range of this quickly changing economic landscape virtual recruiting and remote work are critical for the future of work. To support the active project demands and skills gaps our staffing experts can help you find the best job for you.
Role: Data Integrations Engineer
Location: Remote (Montreal preferred however Toronto is fine as well)
Duration: 1 Year Contract
Job Description:
## About the Role
We are seeking a *Data Integrations Engineer* to own the analysis design and documentation that underpins our data integration pipelines. You will sit at the intersection of source systems and target data models profiling incoming data assessing the impact of new requirements on existing designs and producing the source-to-target mapping (STTM) artifacts that engineering teams build from. Success in this role means new data requirements are validated well-understood and cleanly translated into transformation logic before a line of pipeline code is written.
## Key Responsibilities
- *Source data analysis & profiling* Analyze source data perform data profiling identify gaps anomalies and quality issues and share actionable insights with stakeholders.
- *Impact analysis* Assess how new requirements affect existing systems and data models and clearly document the changes required to current designs.
- *Feasibility assessment* Evaluate whether new requirements are realistic and can fit within the current system architecture and data model and recommend alternatives where they cannot.
- *STTM documentation* Prepare and maintain accurate Source-to-Target Mapping documentation grounded in the target data model.
- *Transformation logic (dimensional)* Apply strong dimensional modeling concepts to define transformation logic within the STTM.
- *Transformation logic (Data Vault) * Leverage Data Vault modeling techniques to define transformation logic within the STTM where applicable.
## Required Skills & Experience
- Proven experience in data analysis data profiling and gap identification across heterogeneous source systems.
- Strong command of *dimensional modeling* (facts dimensions star/snowflake schemas slowly changing dimensions).
- Working knowledge of *Data Vault* modeling (hubs links satellites) and its application to transformation logic.
- Demonstrated ability to perform *impact analysis* on existing data models and systems.
- Hands-on experience authoring *Source-to-Target Mapping (STTM)* documents.
- Solid SQL skills and comfort querying/profiling large datasets.
- Ability to assess requirement feasibility and communicate trade-offs to technical and business stakeholders.
- Strong written communication and documentation discipline.
## Nice to Have
- Familiarity with cloud data platforms (Snowflake Databricks).
- Exposure to data governance lineage and metadata management tooling.
- Experience with data profiling tools and automated data quality frameworks.
## What Success Looks Like
- Source data issues are surfaced early with clear insights that de-risk downstream builds.
- New requirements are validated for feasibility and their impact documented before development begins.
- STTM documents are accurate complete and directly usable by engineering teams.
- Transformation logic reflects sound dimensional and Data Vault modeling practices.
For more information and other jobs available please contact our recruitment team at . To view all the jobs available in the USA and Asia please visit our website at .
Role: Data Integrations Engineer
Location: Remote (Montreal preferred however Toronto is fine as well)
Duration: 1 Year Contract
Job Description:
## About the Role
We are seeking a *Data Integrations Engineer* to own the analysis design and documentation that underpins our data integration pipelines. You will sit at the intersection of source systems and target data models profiling incoming data assessing the impact of new requirements on existing designs and producing the source-to-target mapping (STTM) artifacts that engineering teams build from. Success in this role means new data requirements are validated well-understood and cleanly translated into transformation logic before a line of pipeline code is written.
## Key Responsibilities
- *Source data analysis & profiling* Analyze source data perform data profiling identify gaps anomalies and quality issues and share actionable insights with stakeholders.
- *Impact analysis* Assess how new requirements affect existing systems and data models and clearly document the changes required to current designs.
- *Feasibility assessment* Evaluate whether new requirements are realistic and can fit within the current system architecture and data model and recommend alternatives where they cannot.
- *STTM documentation* Prepare and maintain accurate Source-to-Target Mapping documentation grounded in the target data model.
- *Transformation logic (dimensional)* Apply strong dimensional modeling concepts to define transformation logic within the STTM.
- *Transformation logic (Data Vault) * Leverage Data Vault modeling techniques to define transformation logic within the STTM where applicable.
## Required Skills & Experience
- Proven experience in data analysis data profiling and gap identification across heterogeneous source systems.
- Strong command of *dimensional modeling* (facts dimensions star/snowflake schemas slowly changing dimensions).
- Working knowledge of *Data Vault* modeling (hubs links satellites) and its application to transformation logic.
- Demonstrated ability to perform *impact analysis* on existing data models and systems.
- Hands-on experience authoring *Source-to-Target Mapping (STTM)* documents.
- Solid SQL skills and comfort querying/profiling large datasets.
- Ability to assess requirement feasibility and communicate trade-offs to technical and business stakeholders.
- Strong written communication and documentation discipline.
## Nice to Have
- Familiarity with cloud data platforms (Snowflake Databricks).
- Exposure to data governance lineage and metadata management tooling.
- Experience with data profiling tools and automated data quality frameworks.
## What Success Looks Like
- Source data issues are surfaced early with clear insights that de-risk downstream builds.
- New requirements are validated for feasibility and their impact documented before development begins.
- STTM documents are accurate complete and directly usable by engineering teams.
- Transformation logic reflects sound dimensional and Data Vault modeling practices.
For more information and other jobs available please contact our recruitment team at . To view all the jobs available in the USA and Asia please visit our website at .
Required Experience:
IC
