Role Description Intellectsoft is a software development company delivering innovative solutions since 2007. We operate across North America, Latin America, the Nordic region, the UK, and Europe. We specialize in industries like Fintech, Healthcare, EdTech, Construction, Hospitality, and more, partnering with startups, mid-sized businesses, and Fortune 500 companies to drive innovation and scalability. - 4+ years of professional experience in data engineering - Experience with PostgreSQL and SQL - Data warehouse schemas: bronze, silver, gold, semantic, governance - Power BI as the reporting and dashboarding layer - Power BI Apps, Deployment Pipelines, Paginated Reports - Power Apps / Power Automate integration for action writeback - ETL/ELT ingestion from ERP, CRM, production, budget, quality, catalog, and organization systems - Data quality SQL assertions and acceptance testing - Scheduled daily and hourly refresh pipelines - Role-based access and secure semantic reporting views - Nice-to-have: - Experience with healthcare operational reporting. - Experience building management cockpit, executive KPI, churn risk, client retention, or operational alerting datasets. - Experience supporting action-tracking workflows or writeback patterns using Power Apps, Power Automate, Dataverse, or SharePoint staging. - Experience with orchestration tools such as Airflow, dbt, Dagster, Prefect, cron-based jobs, or cloud-native schedulers. Responsibilities - Design, build, and maintain the reporting data warehouse using a layered model: bronze, silver, gold, semantic, and governance. - Build reliable ELT/ETL pipelines from ERP, CRM, production, budget, quality, catalog, and organization data sources. - Develop and optimize SQL transformations for daily facts, conformed dimensions, KPI views, cohort analytics, client 360 views, alerting views, and operational dashboards. - Maintain semantic views used by Power BI reporting, ensuring business users only access approved reporting layers. - Implement data quality checks, freshness validation, reconciliation tests, and SLA monitoring. - Support daily and hourly refresh pipelines, including incremental refresh logic for operational order and production data. - Implement governance, role-based access, and secure data access patterns for group, lab, clinic, owner, and user-level visibility. - Partner with BI developers to ensure Power BI reports are backed by clean, stable, documented semantic datasets. - Collaborate with business stakeholders to validate KPI definitions, reporting grain, ownership logic, and actionability of alerts. - Maintain documentation for data lineage, metric definitions, pipeline runbooks, and acceptance tests. Benefits - Awesome projects with an impact - Udemy courses of your choice - Team-buildings, events, marathons & charity activities to connect and recharge - Workshops, trainings, expert knowledge-sharing that keep you growing - Clear career path - Absence days for work-life balance - Flexible hours & work setup - work from anywhere and organize your day your way

• Define and lead enterprise data architecture strategy with strong focus on Azure-based modern data platforms and Lakehouse architecture. • Architect, design, and optimize scalable Data Warehouse and analytics solutions using Azure Synapse, Azure Data Lake Storage Gen2, Databricks, Delta Lake, and Microsoft Fabric. • Build and orchestrate robust ETL/ELT pipelines using Azure Data Factory, Synapse Pipelines, PySpark, and modern orchestration frameworks. • Implement Medallion Architecture (Bronze/Silver/Gold) and scalable data ingestion frameworks supporting batch, streaming, and CDC workloads. • Develop enterprise semantic models and optimize datasets for Power BI Premium, Fabric, and self-service analytics. • Establish enterprise standards for data modeling, governance, security, observability, and performance optimization. • Lead Data Warehouse modernization initiatives and implement scalable Star Schema, Snowflake, and Data Vault 2.0 models. • Drive platform scalability, MPP query tuning, workload optimization, and cloud cost optimization initiatives. • Implement CI/CD, DataOps, and Infrastructure-as-Code practices using Azure DevOps, GitHub Actions, Terraform, or Bicep. • Promote AI-assisted engineering practices leveraging GitHub Copilot, Cursor AI, and Azure OpenAI for development productivity and automation. • Mentor engineering teams and drive engineering excellence, automation, and reusable framework adoption.

Role Description We are seeking talented Data & AI Engineers to support the development of an enterprise-grade AI Assistant. This is a high-impact initiative at the intersection of modern data engineering and applied AI. The role focuses on building the data pipeline that transforms unstructured corporate documents into a searchable, intelligent knowledge base powering a Large Language Model (LLM) as well as automating actions such as ticket creation and workflow integrations. - Data Engineering: Build and maintain scalable data pipelines using Databricks and Azure Data Lake Storage Gen2 (ADLS Gen2), ensuring reliability and performance across all pipeline stages. - Data Transformation: Implement the Medallion Architecture (Raw → Silver → Gold layers) to clean, normalise, and structure technical documentation for downstream AI consumption. - AI Orchestration: Design and develop the Reasoning Layer using frameworks such as LangChain or LlamaIndex to manage LLM logic, prompt routing, and tool orchestration. - Search Optimisation: Manage and tune Vector Databases (e.g. Pinecone, Weaviate, or Azure AI Search) to enable fast and accurate semantic retrieval across the corporate knowledge base. - Integration & Automation: Develop Azure Apps and Azure Functions to connect the AI system to external enterprise platforms such as Salesforce and SharePoint, enabling end-to-end automation. Qualifications - 3–4 years in Data Engineering or Software Development with a strong focus on cloud-based data processing. - Strong proficiency in Databricks and Python; comfortable working across the full data engineering lifecycle. - Hands-on experience with LLM orchestration frameworks: LangChain, LlamaIndex, or similar. - Solid understanding of the Azure ecosystem — Storage (ADLS Gen2), Identity (AAD), and Serverless (Azure Functions). - Familiarity with modern AI coding assistants (GitHub Copilot, Cursor, OpenAI Codex) to accelerate development velocity. Company Description Cypher Consulting Europe takes pride in its ability to deliver expert consultants across a wide spectrum of technologies and industry sectors.

• Lead the design and evolution of our enterprise data architecture • Define and lead enterprise data architecture strategy across Azure data platforms, Snowflake, Azure Data Lake, analytics, and integration services • Design scalable, secure, and high-performance data models, pipelines, and platform architectures aligned to business and technical requirements • Establish architecture standards, governance frameworks, and best practices for data quality, lineage, security, and lifecycle management • Oversee solution design reviews, architecture documentation, and implementation guidance for critical data initiatives • Provide technical leadership and mentorship to data engineers, architects, and business intelligence professionals