Senior / Lead Data Engineer Cloud (Terraform, DBT, Azure)

Job description

**Job Title:** Senior / Lead Data Engineer Cloud (Terraform, DBT, Azure) **Key Skills:** DBT, Azure Databricks, Terraform, SQL, Python, Delta Lake, Unity Catalog, AI-Assisted Development, Data Engineering, CI/CD **Experience:** 5+ years of experience. **Location:** Open to candidates across LATAM. **At Coforge, we are looking for a Senior / Lead Data Engineer Cloud (Terraform, DBT, Azure) (#22555) with the following profile.** ### Responsibilities • Design, build, and maintain scalable DBT models on Azure Databricks, delivering curated and governed gold-layer data domains in a production environment. • Develop and optimize data solutions using Delta Lake, Unity Catalog, and Medallion Architecture principles. • Leverage AI-assisted development tools, including Claude Code and similar platforms, for model generation, refactoring, debugging, testing, and documentation. • Build and maintain comprehensive data quality frameworks through DBT tests, validation rules, automated testing, and monitoring practices. • Participate in rapid development and deployment cycles through pull-request-based workflows, AI-supported code reviews, and CI/CD quality gates. • Collaborate with platform and engineering teams to define and implement AI-driven development practices and reusable engineering patterns. • Curate datasets, semantic definitions, business terminology, and analytical assets to support natural-language data consumption and self-service analytics initiatives. • Contribute to the evolution of data engineering best practices, including AI-assisted DBT development, data contracts, observability, and domain-driven ownership models. • Support modernization initiatives through automation, migration acceleration, and AI-powered engineering workflows. • Drive adoption of engineering standards, documentation practices, and scalable delivery methodologies. • Measure and improve the effectiveness of AI-generated code, automated test coverage, and engineering productivity metrics. • Work directly with business stakeholders to ensure delivered data products align with business objectives and quality expectations. ### Mandatory Requirements • 5+ years of experience in Data Engineering. • At least 2 years of hands-on experience building, deploying, and supporting production-grade DBT projects. • Strong expertise in DBT, including models, tests, macros, snapshots, project structure, and large-scale refactoring. • Advanced SQL skills and solid Python programming experience. • Hands-on experience with Azure Databricks, including Delta Lake, Unity Catalog, and Medallion Architecture. • Strong understanding of data modeling, data transformation, and cloud-based analytics platforms. • Experience implementing and managing Infrastructure as Code (IaC) solutions using Terraform. • Strong testing mindset, including DBT testing frameworks, data quality validation, and automated quality controls. • Experience with tools such as dbt-expectations, Great Expectations, or similar testing frameworks. • Experience working with Git-based development workflows, pull requests, code reviews, and CI/CD pipelines. • Familiarity with modern AI coding tools such as Claude Code, GitHub Copilot, Cursor, or similar technologies. • Ability to independently own and deliver data domains from design through production deployment. • Strong communication and stakeholder engagement skills. ### Preferred Requirements • Experience curating Databricks Genie environments or building semantic layers for natural-language analytics. • Experience within insurance, financial services, or other regulated industries. • Knowledge of policy, claims, customer, exposure, or regulatory reporting data domains. • Experience with PySpark for large-scale transformation workloads. • Experience with orchestration technologies such as Databricks Workflows or Apache Airflow. • DBT, Databricks, Azure, or cloud-related certifications. • Experience with Data Observability, Data Contracts, and Domain Ownership frameworks. • Exposure to Databricks DLT (Delta Live Tables), Lakeflow, Asset Bundles, and advanced Databricks capabilities. • Experience implementing AI-assisted migration, modernization, or engineering transformation initiatives. • Familiarity with engineering productivity metrics and AI adoption measurement frameworks. **Published on:** 31-08-2026 At Coforge, we hire professionals solely based on their skills and qualifications and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.