À propos de ce poste Lead Data Engineer (DBT, Databricks, Azure) chez Encora
Responsibilities
• Design and oversee the architecture of low-latency, API-driven data solutions, from backend data models through serving layers and API consumption.
• Build and maintain scalable backend services and REST APIs using Python and object-oriented programming principles.
• Design, develop, and optimize data pipelines using Azure Databricks, DBT, SQL, and cloud-native technologies.
• Own the architecture and implementation of curated data layers, ensuring high availability, scalability, and performance.
• Evaluate, select, and implement technologies for low-latency data serving and API consumption.
• Lead infrastructure deployment and management using Terraform and Infrastructure as Code (IaC) practices.
• Mentor and develop a team of data and machine learning engineers, providing technical guidance, coaching, and career development support.
• Conduct code reviews and establish engineering standards, development best practices, and architectural guidelines.
• Collaborate with Product, Engineering, Business, and Project stakeholders to define technical solutions and delivery roadmaps.
• Ensure data quality, observability, monitoring, alerting, and SLA compliance across all data products and services.
• Drive CI/CD adoption and oversee release management processes for pipelines, services, and platform components.
• Act as the primary technical escalation point for troubleshooting complex production issues and ensuring long-term platform stability.
• Maintain comprehensive technical documentation, architectural decisions, and implementation standards.
Mandatory Requirements
• At least 3 years of experience leading engineering teams, including senior, mid-level, and junior professionals.
• Strong backend development experience with proven delivery of production-grade REST APIs and backend services.
• Expert-level programming skills in Python, including strong object-oriented programming (OOP) principles.
• Extensive experience with PyTest, unit testing, automated testing frameworks, and software quality practices.
• Strong hands-on experience with Azure Databricks and DBT.
• Advanced SQL skills and experience building scalable data solutions.
• Deep understanding of data modeling, dimensional modeling, and consumption-oriented data architectures.
• Extensive experience with Terraform and Infrastructure as Code (IaC) deployments.
• Experience designing and delivering low-latency data products, serving layers, or API-driven data solutions.
• Strong knowledge of CI/CD pipelines, Git-based version control, and modern software engineering practices.
• Proven ability to lead technical delivery while remaining hands-on with architecture, development, and code reviews.
• Excellent communication and stakeholder management skills, with the ability to work effectively across technical and business teams.
Preferred Requirements
• Knowledge of insurance concepts such as policy administration, claims, underwriting, and customer data.
• Experience with Snowflake and Snowflake-to-Databricks integration or migration patterns.
• Hands-on experience with Azure AI Search, Lakebase, feature stores, or similar low-latency serving technologies.
• Experience with streaming and real-time data technologies such as Kafka, Event Hubs, or Delta Live Tables.
• Experience implementing data governance, security, and compliance frameworks.
• Experience managing large-scale DBT environments and terabyte-scale data pipelines.
• Experience leading cloud migration initiatives, particularly AWS-to-Azure migrations.
• Familiarity with machine learning platforms and collaboration with ML engineering teams.