Company Description Blend is a premier AI services provider, committed to creating meaningful impact for its clients through the power of data science, AI, technology, and people. We help organisations solve complex business challenges by combining deep domain understanding with modern data and AI capabilities. Our teams work across strategy, analytics, engineering, and product delivery to create scalable, high-value solutions that improve decision-making, efficiency, and growth. Job Description We are looking for an experienced Senior Data Engineer to support the delivery of a foundational Azure data platform for a large telecommunications client. This role will be central to building and operating the ingestion pipelines, Medallion architecture, and data models that underpin operational reporting across the business. The ideal candidate will have strong hands-on experience in cloud data engineering, pipeline development, data modelling, and working with modern cloud data warehousing platform, whether Databricks or Snowflake. This person will work closely with BI Consultants, DevOps Engineers, and Data Governance leads to ensure that data from priority source systems is reliably ingested, transformed, and delivered as trusted, well-governed datasets that support business decision-making and PIPEDA compliance. Responsibilities - Design, build, and maintain scalable ingestion pipelines from priority source systems into Bronze, Silver, and Gold layers of the Medallion architecture, covering both batch and incremental load patterns. - Complete source-to-target mapping documentation, agree conformed dimensions, taxonomies, and systems of record with the governance workstream, and implement the Gold aggregation layer with KPI metric definitions signed off by business stakeholders. - Model and transform business data across the Medallion layers into structures that support operational Power BI reporting, ensuring Silver and Gold layer tables are optimised for the agreed KPI and reporting requirements. - Apply and maintain governed data access controls in the chosen cloud data platform, including role-based permissions and any column-level or row-level security required to meet PIPEDA compliance obligations as defined by the governance workstream. - Implement robust ingestion, transformation, and data quality processes including automated DQ checks across all Medallion layers, error handling for failed pipeline runs, and end-to-end testing from source systems to the Gold layer. - Drive Silver-to-Gold reconciliation sign-off with business stakeholders, ensuring a single agreed definition for every committed KPI and eliminating cross-department reporting discrepancies. - Complete and maintain the data dictionary for all platform tables, ensuring data is well-documented, accessible, and aligned to business definitions used by BI developers, report authors, and stakeholders during UAT. - Work with architects and client data stakeholders to align designs with enterprise data standards, governance requirements, and long-term maintainability. - Produce data engineering runbooks and handover documentation, including pipeline operational guides and technical documentation structured for the client’s internal team to maintain and extend the platform independently. - Support deployment of data solutions into controlled Dev, Test, and Production environments. - Support continued development of the Medallion architecture in later phases, including additional Bronze, Silver, and Gold datasets, and contribute to pipeline orchestration running reliably on the agreed ingestion schedule. Qualifications - Strong hands-on experience with SQL and Python for data processing and transformation. - Experience building scalable data pipelines and transformation workflows for large, complex datasets. - Strong understanding of data modelling, semantic layer design, and analytical data structures. - Experience with Azure data services, including Azure Data Factory for orchestration and ingestion (including Self-Hosted Integration Runtimes for on-premises connectivity) and Azure Data Lake Storage as a landing zone. - Hands-on experience with a modern cloud data warehousing or lakehouse platform such as Databricks or Snowflake, including building transformation notebooks or jobs, managing compute, and working within a Medallion or equivalent layered architecture. - Experience working with large analytical, transactional, or domain-rich enterprise datasets is highly desirable. - Understanding of governed data access patterns, role-based permissions, and compliance controls, including familiarity with PIPEDA or equivalent Canadian data privacy requirements and how these translate into platform-level access design. - Familiarity with testing, validation, and monitoring for data quality and reliability. - Experience with Git-based CI/CD development workflows. - Strong communication skills and ability to work collaboratively with technical and business stakeholders. Nice to have - Familiarity with Power BI semantic model design and how Gold layer table structures, naming conventions, and relationships affect downstream report development and performance. - Specific experience with Databricks (Unity Catalog, Repos, Delta Live Tables) or Snowflake (Streams, Tasks, Snowpipe) is a strong advantage. - Experience working in regulated enterprise environments, ideally in telecommunications or similarly complex data landscapes, with an understanding of data sensitivity classification and PII handling requirements. - Experience contributing to knowledge transfer and internal capability enablement. What about languages? Advanced English proficiency required. How much experience must I have? 5+ years of experience in Data Engineering, ideally in cloud-based analytical environments. Additional Information Our benefits: Learning Opportunities: - Certifications in AWS (we are AWS Partners), Databricks, and Snowflake. - Access to AI learning paths to stay up to date with the latest technologies. - Study plans, courses, and additional certifications tailored to your role. - Access to Udemy Business, offering thousands of courses to boost your technical and soft skills. - English lessons to support your professional communication. 👩‍🏫 Mentoring and Development: - Career development plans and mentorship programs to help shape your path. 🎁 Celebrations & Support: - Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones. - Company-provided equipment. ⚖️ Flexible working options to help you strike the right balance. Other benefits may vary according to your location in LATAM. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters. So what are the next steps? Our team is eager to learn about you! Send us your resume or LinkedIn profile below and we’ll explore working together!

Company Description Blend is a premier AI services provider, committed to creating meaningful impact for its clients through the power of data science, AI, technology, and people. We help organisations solve complex business challenges by combining deep domain understanding with modern data and AI capabilities. Our teams work across strategy, analytics, engineering, and product delivery to create scalable, high-value solutions that improve decision-making, efficiency, and growth. Job Description We are looking for an experienced Senior Data Engineer to support the delivery of a foundational Azure data platform for a large telecommunications client. This role will be central to building and operating the ingestion pipelines, Medallion architecture, and data models that underpin operational reporting across the business. The ideal candidate will have strong hands-on experience in cloud data engineering, pipeline development, data modelling, and working with modern cloud data warehousing platform, whether Databricks or Snowflake. This person will work closely with BI Consultants, DevOps Engineers, and Data Governance leads to ensure that data from priority source systems is reliably ingested, transformed, and delivered as trusted, well-governed datasets that support business decision-making and PIPEDA compliance. Responsibilities - Design, build, and maintain scalable ingestion pipelines from priority source systems into Bronze, Silver, and Gold layers of the Medallion architecture, covering both batch and incremental load patterns. - Complete source-to-target mapping documentation, agree conformed dimensions, taxonomies, and systems of record with the governance workstream, and implement the Gold aggregation layer with KPI metric definitions signed off by business stakeholders. - Model and transform business data across the Medallion layers into structures that support operational Power BI reporting, ensuring Silver and Gold layer tables are optimised for the agreed KPI and reporting requirements. - Apply and maintain governed data access controls in the chosen cloud data platform, including role-based permissions and any column-level or row-level security required to meet PIPEDA compliance obligations as defined by the governance workstream. - Implement robust ingestion, transformation, and data quality processes including automated DQ checks across all Medallion layers, error handling for failed pipeline runs, and end-to-end testing from source systems to the Gold layer. - Drive Silver-to-Gold reconciliation sign-off with business stakeholders, ensuring a single agreed definition for every committed KPI and eliminating cross-department reporting discrepancies. - Complete and maintain the data dictionary for all platform tables, ensuring data is well-documented, accessible, and aligned to business definitions used by BI developers, report authors, and stakeholders during UAT. - Work with architects and client data stakeholders to align designs with enterprise data standards, governance requirements, and long-term maintainability. - Produce data engineering runbooks and handover documentation, including pipeline operational guides and technical documentation structured for the client’s internal team to maintain and extend the platform independently. - Support deployment of data solutions into controlled Dev, Test, and Production environments. - Support continued development of the Medallion architecture in later phases, including additional Bronze, Silver, and Gold datasets, and contribute to pipeline orchestration running reliably on the agreed ingestion schedule. Qualifications - Strong hands-on experience with SQL and Python for data processing and transformation. - Experience building scalable data pipelines and transformation workflows for large, complex datasets. - Strong understanding of data modelling, semantic layer design, and analytical data structures. - Experience with Azure data services, including Azure Data Factory for orchestration and ingestion (including Self-Hosted Integration Runtimes for on-premises connectivity) and Azure Data Lake Storage as a landing zone. - Hands-on experience with a modern cloud data warehousing or lakehouse platform such as Databricks or Snowflake, including building transformation notebooks or jobs, managing compute, and working within a Medallion or equivalent layered architecture. - Experience working with large analytical, transactional, or domain-rich enterprise datasets is highly desirable. - Understanding of governed data access patterns, role-based permissions, and compliance controls, including familiarity with PIPEDA or equivalent Canadian data privacy requirements and how these translate into platform-level access design. - Familiarity with testing, validation, and monitoring for data quality and reliability. - Experience with Git-based CI/CD development workflows. - Strong communication skills and ability to work collaboratively with technical and business stakeholders. Nice to have - Familiarity with Power BI semantic model design and how Gold layer table structures, naming conventions, and relationships affect downstream report development and performance. - Specific experience with Databricks (Unity Catalog, Repos, Delta Live Tables) or Snowflake (Streams, Tasks, Snowpipe) is a strong advantage. - Experience working in regulated enterprise environments, ideally in telecommunications or similarly complex data landscapes, with an understanding of data sensitivity classification and PII handling requirements. - Experience contributing to knowledge transfer and internal capability enablement. What about languages? Advanced English proficiency required. How much experience must I have? 5+ years of experience in Data Engineering, ideally in cloud-based analytical environments. Additional Information Our benefits: Learning Opportunities: - Certifications in AWS (we are AWS Partners), Databricks, and Snowflake. - Access to AI learning paths to stay up to date with the latest technologies. - Study plans, courses, and additional certifications tailored to your role. - Access to Udemy Business, offering thousands of courses to boost your technical and soft skills. - English lessons to support your professional communication. 👩‍🏫 Mentoring and Development: - Career development plans and mentorship programs to help shape your path. 🎁 Celebrations & Support: - Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones. - Company-provided equipment. ⚖️ Flexible working options to help you strike the right balance. Other benefits may vary according to your location in LATAM. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters. So what are the next steps? Our team is eager to learn about you! Send us your resume or LinkedIn profile below and we’ll explore working together!

Company Description Blend is a premier AI services provider, committed to creating meaningful impact for its clients through the power of data science, AI, technology, and people. We help organisations solve complex business challenges by combining deep domain understanding with modern data and AI capabilities. Our teams work across strategy, analytics, engineering, and product delivery to create scalable, high-value solutions that improve decision-making, efficiency, and growth. Job Description We are looking for an experienced Senior Data Engineer to support the delivery of a foundational Azure data platform for a large telecommunications client. This role will be central to building and operating the ingestion pipelines, Medallion architecture, and data models that underpin operational reporting across the business. The ideal candidate will have strong hands-on experience in cloud data engineering, pipeline development, data modelling, and working with modern cloud data warehousing platform, whether Databricks or Snowflake. This person will work closely with BI Consultants, DevOps Engineers, and Data Governance leads to ensure that data from priority source systems is reliably ingested, transformed, and delivered as trusted, well-governed datasets that support business decision-making and PIPEDA compliance. Responsibilities - Design, build, and maintain scalable ingestion pipelines from priority source systems into Bronze, Silver, and Gold layers of the Medallion architecture, covering both batch and incremental load patterns. - Complete source-to-target mapping documentation, agree conformed dimensions, taxonomies, and systems of record with the governance workstream, and implement the Gold aggregation layer with KPI metric definitions signed off by business stakeholders. - Model and transform business data across the Medallion layers into structures that support operational Power BI reporting, ensuring Silver and Gold layer tables are optimised for the agreed KPI and reporting requirements. - Apply and maintain governed data access controls in the chosen cloud data platform, including role-based permissions and any column-level or row-level security required to meet PIPEDA compliance obligations as defined by the governance workstream. - Implement robust ingestion, transformation, and data quality processes including automated DQ checks across all Medallion layers, error handling for failed pipeline runs, and end-to-end testing from source systems to the Gold layer. - Drive Silver-to-Gold reconciliation sign-off with business stakeholders, ensuring a single agreed definition for every committed KPI and eliminating cross-department reporting discrepancies. - Complete and maintain the data dictionary for all platform tables, ensuring data is well-documented, accessible, and aligned to business definitions used by BI developers, report authors, and stakeholders during UAT. - Work with architects and client data stakeholders to align designs with enterprise data standards, governance requirements, and long-term maintainability. - Produce data engineering runbooks and handover documentation, including pipeline operational guides and technical documentation structured for the client’s internal team to maintain and extend the platform independently. - Support deployment of data solutions into controlled Dev, Test, and Production environments. - Support continued development of the Medallion architecture in later phases, including additional Bronze, Silver, and Gold datasets, and contribute to pipeline orchestration running reliably on the agreed ingestion schedule. Qualifications - Strong hands-on experience with SQL and Python for data processing and transformation. - Experience building scalable data pipelines and transformation workflows for large, complex datasets. - Strong understanding of data modelling, semantic layer design, and analytical data structures. - Experience with Azure data services, including Azure Data Factory for orchestration and ingestion (including Self-Hosted Integration Runtimes for on-premises connectivity) and Azure Data Lake Storage as a landing zone. - Hands-on experience with a modern cloud data warehousing or lakehouse platform such as Databricks or Snowflake, including building transformation notebooks or jobs, managing compute, and working within a Medallion or equivalent layered architecture. - Experience working with large analytical, transactional, or domain-rich enterprise datasets is highly desirable. - Understanding of governed data access patterns, role-based permissions, and compliance controls, including familiarity with PIPEDA or equivalent Canadian data privacy requirements and how these translate into platform-level access design. - Familiarity with testing, validation, and monitoring for data quality and reliability. - Experience with Git-based CI/CD development workflows. - Strong communication skills and ability to work collaboratively with technical and business stakeholders. Nice to have - Familiarity with Power BI semantic model design and how Gold layer table structures, naming conventions, and relationships affect downstream report development and performance. - Specific experience with Databricks (Unity Catalog, Repos, Delta Live Tables) or Snowflake (Streams, Tasks, Snowpipe) is a strong advantage. - Experience working in regulated enterprise environments, ideally in telecommunications or similarly complex data landscapes, with an understanding of data sensitivity classification and PII handling requirements. - Experience contributing to knowledge transfer and internal capability enablement. What about languages? Advanced English proficiency required. How much experience must I have? 5+ years of experience in Data Engineering, ideally in cloud-based analytical environments. Additional Information Our benefits: Learning Opportunities: - Certifications in AWS (we are AWS Partners), Databricks, and Snowflake. - Access to AI learning paths to stay up to date with the latest technologies. - Study plans, courses, and additional certifications tailored to your role. - Access to Udemy Business, offering thousands of courses to boost your technical and soft skills. - English lessons to support your professional communication. 👩‍🏫 Mentoring and Development: - Career development plans and mentorship programs to help shape your path. 🎁 Celebrations & Support: - Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones. - Company-provided equipment. ⚖️ Flexible working options to help you strike the right balance. Other benefits may vary according to your location in LATAM. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters. So what are the next steps? Our team is eager to learn about you! Send us your resume or LinkedIn profile below and we’ll explore working together!

Role Description Connections Foodservice is looking for a Senior Data Strategist who lives at the intersection of analytics and storytelling. In this role, you'll be the analytical backbone of our B2B foodservice marketing operation — transforming raw data from platforms like GA4, Salesforce, and HubSpot into clear, compelling narratives that drive smarter decisions for our clients and internal teams. This isn't a purely heads-down analyst role. We need someone who can pull the numbers and walk into a (virtual) room with clients or internal leadership and explain what they mean, why they matter, and what we should do next. You'll own day-to-day marketing performance reporting while also acting as a thought leader — evaluating and championing new tools, methodologies, and visualization approaches (like Tableau) that push our reporting capabilities forward. If you're energized by the challenge of making complex data accessible, you're curious about the foodservice industry, and you want a role where your strategic voice is genuinely heard, this is the seat for you. Responsibilities - Reporting & Analytics - Build, maintain, and optimize marketing performance reports using Google Analytics 4 (GA4), pulling actionable insights specific to B2B foodservice audiences and campaign objectives. - Develop and manage dashboards and reports within Salesforce and HubSpot to track pipeline influence, lead quality, campaign attribution, and sales-marketing alignment. - Synthesize data across multiple platforms into unified, cohesive performance snapshots for both internal stakeholders and external client reporting. - Data Storytelling & Strategy - Translate complex datasets into clear, narrative-driven reports that connect marketing and communication initiatives to business outcomes — not just metrics. - Present findings to clients and internal teams with confidence, framing data within the broader context of B2B foodservice marketing strategy — acting as a trusted analytical partner on both sides. - Develop a consistent reporting voice and standard for how Connections Foodservice communicates marketing performance internally and to clients. - Tools, Innovation & Thought Leadership - Serve as an internal champion for data visualization best practices, leading the adoption and development of Tableau (or comparable platforms) to elevate how we present data. - Proactively research, evaluate, and recommend emerging tools and technologies that improve reporting accuracy, efficiency, and insight depth. - Stay current on trends in B2B marketing analytics, CRM reporting, and foodservice industry benchmarks — bringing outside perspective to internal strategy conversations. - Cross-Functional Collaboration - Partner closely with account, creative, and marketing strategy teams to ensure data is informing — not just documenting — campaign decisions. - Collaborate with sales leadership to align marketing metrics with CRM data, improving visibility into full-funnel performance. - Help define KPIs and measurement frameworks at the outset of campaigns and initiatives, not just after the fact. - Day-to-Day Operations - Manage a regular cadence of weekly, monthly, and quarterly reporting deliverables. - Maintain data hygiene and integrity across reporting platforms, flagging discrepancies and working cross-functionally to resolve them. - Document processes, reporting templates, and data governance standards to build institutional knowledge and scalability. Qualifications - 4–7 years of experience in a marketing analytics, data strategy, or similar role — preferably in an agency or B2B environment. - Hands-on proficiency with GA4, HubSpot, and Salesforce reporting and analytics. - Experience building dashboards and visualizations in Tableau or a comparable BI tool (Power BI, Looker, Datorama/ Marketing Cloud Intelligence tools, etc.). - Strong ability to communicate data findings to non-technical audiences — written, visual, and verbal. - Experience in or exposure to the foodservice, CPG, or B2B marketing space is a plus. - Exceptional written and verbal communication skills, with the ability to present data findings confidently to clients and leadership in a fully remote environment — through video calls, written reports, and async deliverables. - Self-directed with a track record of identifying opportunities for improvement and following through independently. - Comfortable operating in ambiguity and building structure where it doesn't yet exist.