Data Engineering Architect

Description

**Data Engineering Architect** We are seeking a professional to define and evolve data architectures, ensuring efficiency, scalability, and alignment with best practices in governance, FinOps, and integration with AI platforms (ML/GenAI). You will support strategic initiatives from project conception, translating business needs into robust, sustainable technical solutions. You will also develop data ingestion and processing pipelines, applying DataOps principles to ensure automation, resilience, data quality, and continuous process monitoring. **Key Responsibilities** * Design and evolve data architectures: Define standards, best practices, and strategies to ensure efficiency and scalability, including FinOps, governance, and integration across AI platforms (ML/GenAI). * Enable data initiatives: Engage from project inception, collaborating with business areas to understand requirements and translate functional needs into robust technical solutions. * Build solutions for data ingestion and processing. * Develop resilient and scalable pipelines, applying DataOps concepts to ensure quality, automation, and continuous monitoring. **Mandatory Requirements and Qualifications** * Proven experience in data engineering within large-scale environments. * Proficiency in analytical data architecture and modeling (Data Lake, Data Warehouse, Lakehouse, Data Mesh). * Strong expertise in Big Data and distributed processing technologies (Spark). * Advanced SQL knowledge and experience optimizing complex queries. * Advanced programming skills in Python and pySpark. * Experience with AWS cloud data services (Glue, EMR, Lake Formation, Redshift, S3, Step Functions, etc.) and DataOps and FinOps practices. * Experience with ETL/ELT pipelines (dbt, Glue) and orchestration tools (Airflow, Step Functions). * Familiarity with microservices, APIs, containers, and messaging systems (Kafka, Kinesis). * Knowledge of governance, security, and compliance in mission-critical environments. * Software engineering best practices (version control, CI/CD, testing). * Ability to translate business concepts into quantitative metrics (KPIs/OKRs). * Experience in technical mentoring and team leadership. Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or Systems Analysis—or currently pursuing such a degree. **Desirable Requirements and Qualifications** * Prior experience in AI environments (data preparation for ML/GenAI).