Addepto is a leading AI consulting (https://addepto.com/ai-consulting/) and data engineering (https://addepto.com/data-engineering-services/) company that builds scalable, ROI-focused AI solutions for some of the world's largest enterprises and pioneering startups, including Rolls Royce, Continental, Porsche, ABB, and WGU. With an exclusive focus on Artificial Intelligence and Big Data, Addepto helps organizations unlock the full potential of their data through systems designed for measurable business impact and long-term growth.
The company's work extends beyond client engagements. Drawing from real-world challenges and insights, Addepto has developed its own product - ContextClue - and actively contributes open-source solutions to the AI community. This commitment to transforming practical experience into scalable innovation has earned Addepto recognition by Forbes as one of the top 10 AI consulting companies worldwide.
As part of KMS Technology, a US-based global technology group, Addepto combines deep AI specialization with enterprise-scale delivery capabilities—enabling the partnership to move clients from AI experimentation to production impact, securely and at scale.
As a Data Engineer, you will have the opportunity to support and further develop an Azure-based data integration solution built primarily around Azure Data Factory (ADF). The current environment includes Azure Functions and ingestion components, but daily delivery is strongly centered on ADF pipeline design, orchestration, monitoring, and continuous improvement.
The project focuses on expanding and stabilizing the existing data platform, including the warehouse layer (Azure SQL Database or Synapse), optional dbt-based transformations, and occasional Power BI reporting support. You will work closely with the client-side Product Owner and Architect, proactively aligning business needs with technical implementation decisions and ensuring high-quality, scalable solutions. Additionally, you will contribute to Azure DevOps CI/CD pipelines and release processes to maintain reliable deployments across environments.
🚀 Your main responsibilities:
Design, develop, and maintain Azure Data Factory pipelines, including orchestration, parameterization, and trigger management.
Configure and manage linked services and datasets within ADF.
Monitor, troubleshoot, and optimize ADF pipelines to ensure performance and reliability.
Develop and maintain ETL/ELT processes and support the evolution of the data warehouse layer (Azure SQL Database or Synapse).
Translate business requirements into technical solutions in close collaboration with the Product Owner and Architect.
Develop and maintain Python-based components (e.g., Azure Functions, API integrations, automation scripts).
Contribute to CI/CD processes in Azure DevOps, including pipelines, releases, and environment promotion.
Support occasional Power BI reporting and dashboarding needs.
Ensure proactive communication, stakeholder alignment, and visibility of risks and impacts.
Take ownership of assigned tasks and actively contribute to continuous platform improvement.
Desenvolve pipelines de dados de segurança, modela grafos de caminhos de ataque e mantém consultas Cypher seguras, apoiando iniciativas de RAG, Text-to-SQL e laboratório isolado.
Build and maintain batch and streaming data pipelines, ETL workflows, and data warehouse solutions, improving data quality, reliability, and performance through Python, SQL, BigQuery, and Airflow.
Design and build scalable data pipelines using Python, Apache Spark, and Databricks, while modernizing legacy systems and ensuring data quality and reliability.
Design, build, and maintain production data pipelines and analytics-ready datasets, optimizing data quality, performance, and reliability while supporting reporting and business stakeholders.
Build and optimize cloud data pipelines, dbt models, and analytical datasets across data warehouse modernization, BI migrations, CRM integrations, and commercial analytics projects.
