Join Zepz: Breaking Down Borders, Together Our Meaningful MissionAt Zepz, we're all about breaking down barriers for our customers and our teammates. Our purpose is deeply personal, we provide a lifeline and deliver opportunities to cross-border communities that need it most through cutting edge finance and tech. Zepz is the power behind WorldRemit and Sendwave, driven by the mission to celebrate the incredible impact migrants have, both at home and abroad. We're not just moving money; we're building a world that truly recognizes and supports global connections.Who You'll Be JoiningWe look for mission-driven builders who thrive in a fast-paced environment connected to a true purpose. We’re an always developing team of experts that enjoy problem solving and bring clarity to tough challenges. At Zepz, we are Relentless Learners, always seeking feedback, and Responsible Owners, treating company resources like your own. We depend on Transparent Communicators who keep the team aligned through open, honest talk.Our Core Commitments — What We Live ByOur vibrant and truly diverse culture is built on three core commitments, that guide how we work and interact: - Integrity: We always do the right thing. It’s simple, but it’s the foundation of everything we build for our customers and each other. - Outcomes: We work for our customers. Their success and prosperity are the results we focus on delivering. - Velocity: We are fast! We maintain high energy levels and make smart decisions quickly, keeping us nimble and ahead of the curve. Perks of Joining Our TeamWe believe in empowering colleagues because we genuinely trust our team. Our culture is founded on this high trust, which naturally encourages the high ownership that drives us to meet our shared high expectations and deliver high performance. Our remote-first culture means you have the flexibility to work in your employing country wherever you feel the most focused and productive. This freedom comes with wonderful tailored, location-specific perks designed to support your whole life, not just your work. Think unlimited annual leave , great healthcare benefits, and employee discounts. We want you to thrive and focus entirely on making your biggest impact! In turn, we expect you to bring high ownership and commitment to your work. This is a place where we value trust and high performance, and we'll provide the environment and support needed for you to excel. About the Role We are looking for a Senior Data Analytics Engineer to help us optimize our business strategy using the latest data techniques. This role is key to setting the roadmap for a highly efficient and scalable data function that will grow with the ambitious plans for the business. Reporting to Product, you will collaborate with Product, Engineering, Data Science, and the wider organization. You will build and maintain new data models, optimize existing ones, and work with a wide variety of technologies and datasets to drive real insight and recommendations. You'll be a driving force in identifying trends, quantifying opportunities, and setting the requirements to develop data-driven solutions that have a direct impact on the business. Our current Data Platform tech stack includes: - Data Lakehouse: Databricks - Cloud & Infrastructure: AWS (S3, Lambda), Kubernetes - Data Processing: Python is our primary language - Orchestration & Transformation: dbt, Fivetran, and Airflow - Visualization: Mode and similar BI tools - Data monitoring and alerting: Metaplane What You'll Do - Data Modeling & Pipelines: Build and maintain scalable and reliable data models to expose high-quality data for analysis and reporting. Where needed, deliver dashboards to drive more self service on data among teams. - Stakeholder Collaboration: Work closely with analysts and business stakeholders to understand commercial requirements, translating them into technical solutions that enable reliable self-serve data for decision-making. - Strategic Analysis: Work in a collaborative, cross-functional way to identify and quantify opportunities, enabling data-driven business decisions and identifying opportunities for improvement through analysis, A/B testing, and tracking, with a strong emphasis on extracting actionable, in-depth business insights. - Data Governance & Quality: Ensure all data and output is of high quality — tested, automated, scalable, and well-documented. You will develop standards and best practices for data consumption and educate data consumers. - Champion Data Culture: Champion the use of data to optimize business performance and bring fresh analytical ideas to the table. - Communication & Presentation: Present results and complex concepts back to the business in a structured, data-driven manner, simplifying them for non-technical audiences. - Process Improvement: Identify opportunities to reduce complexity and increase efficiency across our data models and data warehouse infrastructure. - Data Cleansing & Transformation: Develop and implement robust data cleansing, validation, and transformation processes to ensure the accuracy, consistency, and reliability of data across all sources. - Insight Storytelling: Translate complex analytical findings into clear, compelling narratives and visualizations for both technical and non-technical audiences, influencing strategic decision-making. What We’re Looking For From You - You are highly proficient with daily use of SQL and have hands-on experience in a modern cloud data warehouse/ lakehouse environment (e.g., Databricks, BigQuery, Redshift, Snowflake). - You’re comfortable automating processes and developing production-standard Python scripts to extract data, perform analysis, and build pipelines. - You have the ability to work confidently with the tools of modern software engineering, such as the command line, version control (Git), testing, and performing code reviews. - You have a problem-solving approach that gets to the underlying business questions, using a variety of data sources and information to find the answer. - You see yourself as a strategic partner who wants to understand the business problem and can clearly communicate the commercial impact of your technical solutions. - You are an advocate for data-driven decision-making who strives to improve processes, establish best practices, and define standards. - You are passionate about learning, able to quickly adopt new business concepts and technologies, and are an independent, curious person who likes to take initiative. - You have an open mind with respect to diversity and inclusivity. Our team (and customers) come from all over the world. Bonus Points - You have familiarity with dbt to design and implement data models. - Experience with data orchestration tools - AML Transaction Monitoring definition, calibration, testing and documentation. Experience with regulatory testing regimes such as DFS rule 504 a plus. - Customer risk rating definition, calibration, testing and documentation. If you want to join us in our journey to help break barriers in financial access and improve lives globally, there's no better place or time to join. Our global team of 800+ people is spread across six continents. We aspire to hire the best mix of people from former Olympians to YouTube influencers and we speak over twenty languages. This incredible diversity isn't a bonus; it's the engine that lets us serve the world. Ready to Apply? Let’s Go.

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!