1 to 25 of 30 Semantic Layer Jobs

analytical and operational systems. Develop, test, and deploy automated data workflows and orchestration using tools such as Airflow, DBT, or similar frameworks. Build, maintain, and enhance data models and semantic layers to support BI, analytics, and AI initiatives. Collaborate with analysts and business teams to develop and evolve dashboards and reports, enabling clear, actionable insight. Contribute to the solution More ❯

metric definitions. • Convert legacy report logic into clear specifications aligned with modern data models and Power BI architecture. • Contribute to the definition of data elements and assist in designing semantic layers that enable scalable and consistent reporting. • Develop and maintain mapping documentation between legacy data structures and new enterprise data warehouse schemas. • Collaborate with data engineers and solution architects More ❯

What you'll be doing: Build and maintain scalable data pipelines using Azure Data Factory and Databricks Develop transformation workflows in dbt, SQL, and Python Design dimensional models and semantic layers to support analytics use cases Implement automated data quality checks, monitoring, and alerting systems - linking issues to business impact Create reusable data assets and documentation to support self More ❯

scalable, modular, reusable, and aligned with enterprise architecture and data strategy. Lead the selection and integration of appropriate technologies and platforms (e.g., data lakes, warehouses, real-time processing, APIs, semantic layers). Data Product Development Collaborate with product managers and data teams to translate business needs into technical data product designs. Architect solutions that support data discoverability, governance, lineage More ❯

scalable, modular, reusable, and aligned with enterprise architecture and data strategy. Lead the selection and integration of appropriate technologies and platforms (e.g., data lakes, warehouses, real-time processing, APIs, semantic layers). Data Product Development Collaborate with product managers and data teams to translate business needs into technical data product designs. Architect solutions that support data discoverability, governance, lineage More ❯

scalable, modular, reusable, and aligned with enterprise architecture and data strategy. Lead the selection and integration of appropriate technologies and platforms (e.g., data lakes, warehouses, real-time processing, APIs, semantic layers). Data Product Development Collaborate with product managers and data teams to translate business needs into technical data product designs. Architect solutions that support data discoverability, governance, lineage More ❯

Define the enterprise-wide data and Business Intelligence strategy aligned with business priorities Partner with CIO/CDO to industrialize analytics and create scalable, sustainable solutions. Design data models, semantic layers, and curated datasets that feed Tableau and other BI tools. Ensure integration of Tableau with enterprise data platforms (Snowflake, Databricks, AWS, etc.). Promote standardized KPIs and metadata More ❯

technology Extensive experience designing fact and dimension tables across domains such as policy, quote, claims, pricing, and fraud, ensuring consistency and alignment with business metrics Deep practical knowledge of semantic layer design and implementation using DBT, SQL, and Delta Live Tables Strong background in building high-performance, scalable data models that support self-service BI and regulatory reporting More ❯

technology Extensive experience designing fact and dimension tables across domains such as policy, quote, claims, pricing, and fraud, ensuring consistency and alignment with business metrics Deep practical knowledge of semantic layer design and implementation using DBT, SQL, and Delta Live Tables Strong background in building high-performance, scalable data models that support self-service BI and regulatory reporting More ❯

in designing and building scalable, future-proof data assets within the Microsoft Azure ecosystem. This role involves technical consulting, hands-on development, and leadership in data modelling, orchestration, and semantic layer design. Key Responsibilities: Provide technical consulting to the Data Engineering Manager during the design phase. Collaborate with a small team of Business Data Engineers to build new … data assets. Lead the design and development of dimensional data models and Power BI semantic models. Replace legacy SAP Business Objects universes with modern Azure-based solutions. Utilize Azure Data Factory (ADF), stored procedures, and Azure Synapse for data processing. Guide the team on best practices, architecture, and documentation standards. Engage with stakeholders to ensure solutions are aligned with … of experience in data engineering, BI, or data architecture roles. Strong expertise in Azure Synapse, ADF, SQL, and Power BI. Proven experience in designing and implementing dimensional models and semantic layers. Familiarity with metadata management tools (e.g., Collibra) and model curation tools (e.g., Tabular Editor). Excellent communication and stakeholder management skills. Experience working in agile environments and leading More ❯

Responsibilities: Design and maintain scalable data platforms using cloud-native technologies such as Databricks and AWS across development, staging, and production environments Build and govern dimensional data models and semantic layers to power consistent and trusted analytics Integrate data from diverse sources including cloud warehouses, APIs, and operational systems Define semantic layers using dbt and Delta Live Tables … complex business processes into scalable and intuitive data models that support analytics and AI Extensive experience designing fact and dimension tables across core business domains Deep practical knowledge of semantic layer design using dbt, SQL, and Delta Live Tables Experience building and maintaining data pipelines across batch and streaming environments Strong understanding of governance frameworks, access controls, and More ❯

Responsibilities: Design and maintain scalable data platforms using cloud-native technologies such as Databricks and AWS across development, staging, and production environments Build and govern dimensional data models and semantic layers to power consistent and trusted analytics Integrate data from diverse sources including cloud warehouses, APIs, and operational systems Define semantic layers using dbt and Delta Live Tables … complex business processes into scalable and intuitive data models that support analytics and AI Extensive experience designing fact and dimension tables across core business domains Deep practical knowledge of semantic layer design using dbt, SQL, and Delta Live Tables Experience building and maintaining data pipelines across batch and streaming environments Strong understanding of governance frameworks, access controls, and More ❯

you'll be doing: Own the analytics platform end-to-end: set the roadmap for models, metrics and data contracts; choose/evolve tooling and standards. Build the golden layer: design high-trust dbt marts and a documented semantic layer that powers product features Ship with reliability: stand up observability (tests, freshness, lineage, cost), enforce SLAs, and More ❯

Microsoft AI certifications/training (AI-102/AI-900/DW-104). Experience designing and deploying AI-powered dashboards using Power BI. Understanding of data modelling and semantic layer design to support intelligent analytics. Ability to integrate AI outputs into reporting pipelines for real-time or predictive insights. Knowledge of DAX and Power Query in the More ❯

Microsoft AI certifications/training (AI-102/AI-900/DW-104). Experience designing and deploying AI-powered dashboards using Power BI. Understanding of data modelling and semantic layer design to support intelligent analytics. Ability to integrate AI outputs into reporting pipelines for real-time or predictive insights. Knowledge of DAX and Power Query in the More ❯

BigQuery architecture, optimization, and cost management Advanced SQL skills and production-level experience using dbt (or similar tools) to build modular, testable transformation pipelines Practical mastery of LookML and semantic layer design within Looker, including Explores, joins, derived tables, and scalability best practices It will also help you to have Experience establishing and enforcing data governance standards through More ❯

Looker) Strong in data modeling, streaming, AI/ML pipelines, and governance Key Responsibilities Design scalable, secure data platforms (SQL/NoSQL, lakehouse, data mesh) Build real-time pipelines, semantic layers, and feature stores Implement governance, privacy, and compliance frameworks Collaborate across teams and mentor engineers More ❯

mentor two Data Engineers, providing technical guidance and coaching. Design and deploy modern data pipelines using Databricks and Azure. Transform unstructured external data into clean, business-ready models. Build semantic layers and embed Unity Catalog for robust data governance. Guide the team in taking Databricks from development to production. Support Terraform adoption and infrastructure-as-code practices. Why This … days/week onsite. What We're Looking For Proven technical leadership in data engineering teams. Deep experience with Databricks, Azure, SQL, and ideally Python. Strong understanding of MDM, semantic modeling, and Unity Catalog. Ability to handle messy, unstructured data and build scalable solutions. Comfortable mentoring and guiding a small, agile team. Finance sector experience is a bonus-but … not essential. Interview Process Initial coffee chat to explore team fit and technical challenges. Technical interview covering Databricks, MDM, semantic layers, pipeline design, and governance. This is a rare opportunity to lead, build, and shape the future of data in a growing financial services business. Ready to make your mark? Let's talk. Modis International Ltd acts as an More ❯

mentor two Data Engineers, providing technical guidance and coaching. Design and deploy modern data pipelines using Databricks and Azure. Transform unstructured external data into clean, business-ready models. Build semantic layers and embed Unity Catalog for robust data governance. Guide the team in taking Databricks from development to production. Support Terraform adoption and infrastructure-as-code practices. Why This … days/week onsite. What We're Looking For Proven technical leadership in data engineering teams. Deep experience with Databricks, Azure, SQL, and ideally Python. Strong understanding of MDM, semantic modeling, and Unity Catalog. Ability to handle messy, unstructured data and build scalable solutions. Comfortable mentoring and guiding a small, agile team. Finance sector experience is a bonus-but … not essential. Interview Process Initial coffee chat to explore team fit and technical challenges. Technical interview covering Databricks, MDM, semantic layers, pipeline design, and governance. This is a rare opportunity to lead, build, and shape the future of data in a growing financial services business. Ready to make your mark? Let's talk. Modis International Ltd acts as an More ❯

mentor two Data Engineers, providing technical guidance and coaching. Design and deploy modern data pipelines using Databricks and Azure. Transform unstructured external data into clean, business-ready models. Build semantic layers and embed Unity Catalog for robust data governance. Guide the team in taking Databricks from development to production. Support Terraform adoption and infrastructure-as-code practices. Why This … days/week onsite. What We're Looking For Proven technical leadership in data engineering teams. Deep experience with Databricks, Azure, SQL, and ideally Python. Strong understanding of MDM, semantic modeling, and Unity Catalog. Ability to handle messy, unstructured data and build scalable solutions. Comfortable mentoring and guiding a small, agile team. Finance sector experience is a bonus-but … not essential. Interview Process Initial coffee chat to explore team fit and technical challenges. Technical interview covering Databricks, MDM, semantic layers, pipeline design, and governance. This is a rare opportunity to lead, build, and shape the future of data in a growing financial services business. Ready to make your mark? Let's talk. Modis International Ltd acts as an More ❯

mentor two Data Engineers, providing technical guidance and coaching. Design and deploy modern data pipelines using Databricks and Azure. Transform unstructured external data into clean, business-ready models. Build semantic layers and embed Unity Catalog for robust data governance. Guide the team in taking Databricks from development to production. Support Terraform adoption and infrastructure-as-code practices. Why This … days/week onsite. What We're Looking For Proven technical leadership in data engineering teams. Deep experience with Databricks, Azure, SQL, and ideally Python. Strong understanding of MDM, semantic modeling, and Unity Catalog. Ability to handle messy, unstructured data and build scalable solutions. Comfortable mentoring and guiding a small, agile team. Finance sector experience is a bonus-but … not essential. Interview Process Initial coffee chat to explore team fit and technical challenges. Technical interview covering Databricks, MDM, semantic layers, pipeline design, and governance. This is a rare opportunity to lead, build, and shape the future of data in a growing financial services business. Ready to make your mark? Let's talk. Modis International Ltd acts as an More ❯

in designing and building scalable, future-proof data assets within the Microsoft Azure ecosystem. This role involves technical consulting, hands-on development, and leadership in data modelling, orchestration, and semantic layer design click apply for full job details More ❯

Bonus & Benefits – FinTech Overview: An established global FinTech organisation is seeking a skilled Senior Analytics Engineer/Data Engineer to help define and manage its analytical data models and semantic layers. You will support the development of reliable, well-structured datasets that enable accurate reporting, improved data accessibility, and better decision-making across the business. Fluent Russian language skills … are essential for this role. Role & Responsibilities: Build and maintain scalable semantic/analytics layers to create consistent business metrics and definitions. Work with teams across the business to understand requirements and translate them into reliable models. Develop core data models following modern data warehouse principles. Write high-quality SQL and maintain dbt-based transformations, tests, and documentation. Support … business requirements into logical, scalable data models. Knowledge of cloud data platforms (e.g., Snowflake, Redshift, BigQuery). Strong communication and documentation skills. Structured, detail-oriented mindset. Desirable: Experience with semantic modelling tools (e.g., dbt SL, LookML). Familiarity with workflow orchestration and BI tooling. Version control experience (Git). Python for scripting. Offer Details: Type: Permanent Location: London/ More ❯

Bonus & Benefits – FinTech Overview: An established global FinTech organisation is seeking a skilled Senior Analytics Engineer/Data Engineer to help define and manage its analytical data models and semantic layers. You will support the development of reliable, well-structured datasets that enable accurate reporting, improved data accessibility, and better decision-making across the business. Fluent Russian language skills … are essential for this role. Role & Responsibilities: Build and maintain scalable semantic/analytics layers to create consistent business metrics and definitions. Work with teams across the business to understand requirements and translate them into reliable models. Develop core data models following modern data warehouse principles. Write high-quality SQL and maintain dbt-based transformations, tests, and documentation. Support … business requirements into logical, scalable data models. Knowledge of cloud data platforms (e.g., Snowflake, Redshift, BigQuery). Strong communication and documentation skills. Structured, detail-oriented mindset. Desirable: Experience with semantic modelling tools (e.g., dbt SL, LookML). Familiarity with workflow orchestration and BI tooling. Version control experience (Git). Python for scripting. Offer Details: Type: Permanent Location: London/ More ❯

Bonus & Benefits – FinTech Overview: An established global FinTech organisation is seeking a skilled Senior Analytics Engineer/Data Engineer to help define and manage its analytical data models and semantic layers. You will support the development of reliable, well-structured datasets that enable accurate reporting, improved data accessibility, and better decision-making across the business. Fluent Russian language skills … are essential for this role. Role & Responsibilities: Build and maintain scalable semantic/analytics layers to create consistent business metrics and definitions. Work with teams across the business to understand requirements and translate them into reliable models. Develop core data models following modern data warehouse principles. Write high-quality SQL and maintain dbt-based transformations, tests, and documentation. Support … business requirements into logical, scalable data models. Knowledge of cloud data platforms (e.g., Snowflake, Redshift, BigQuery). Strong communication and documentation skills. Structured, detail-oriented mindset. Desirable: Experience with semantic modelling tools (e.g., dbt SL, LookML). Familiarity with workflow orchestration and BI tooling. Version control experience (Git). Python for scripting. Offer Details: Type: Permanent Location: London/ More ❯