This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
We are looking for a skilled GenAI Data Automation Engineer to design and implement innovative, AI-driven automation solutions across AWS and Azure hybrid environments. You will be responsible for building intelligent, scalable data pipelines and automations that integrate cloud services, enterprise tools, and Generative AI to support mission-critical analytics, reporting, and customer engagement platforms. Ideal candidate is mission focused, delivery oriented, applies critical thinking to create innovative functions and solve technical issues. This position involves designing, developing, testing, and troubleshooting software programs to enhance existing systems and build new software products. The ideal candidate will apply software engineering principles and collaborate effectively with colleagues to tackle moderately complex technical challenges and deliver impactful solutions.
Job Responsibility:
Design and maintain data pipelines in AWS using S3, RDS/SQL Server, Glue, Lambda, EMR, DynamoDB, and Step Functions
Develop ETL/ELT processes to move data from multiple data systems including DynamoDB → SQL Server (AWS) and between AWS ↔ Azure SQL systems
Integrate AWS Connect, Nice inContact CRM data into the enterprise data pipeline for analytics and operational reporting
Engineer, enhance ingestion pipelines with Apache Spark, Flume, Kafka for real-time and batch processing into Apache Solr, AWS Open Search platforms
Leverage Generative AI services and Frameworks (AWS Bedrock, Amazon Q, Azure OpenAI, Hugging Face, LangChain) to: Create automated processes for vector generation and embedding from unstructured data to support Generative AI models
Automate data quality checks, metadata tagging, and lineage tracking
Enhance ingestion/ETL with LLM-assisted transformation and anomaly detection
Build conversational BI interfaces that allow natural language access to Solr and SQL data
Develop AI-powered copilots for pipeline monitoring and automated troubleshooting
Implement SQL Server stored procedures, indexing, query optimization, profiling, and execution plan tuning to maximize performance
Apply CI/CD best practices using GitHub, Jenkins, or Azure DevOps for both data pipelines and GenAI model integration
Ensure security and compliance through IAM, KMS encryption, VPC isolation, RBAC, and firewalls
Support Agile DevOps processes with sprint-based delivery of pipeline and AI-enabled features
Requirements:
BS in Computer Science or related field with 2+ years of data engineering, automation experiences
Hands-on experience with LLM, Generative AI frameworks using AWS Bedrock, Azure OpenAI or open source platform
Hands-on experience with SQL, SSIS, Python, Spark, Bash, Power shell, AWS/Azure CLIs
Experience with AWS services like S3, RDS/SQL Server, Glue, Lambda, EMR, DynamoDB
Familiarity with Apache Flume, Kafka, Solr for large-scale data ingestion and search
Experience with integrating REST API calls in data pipelines and workflows
Familiarity with JIRA, GitHub / Azure DevOps / Jenkins for SDLC and CI/CD automation
Strong troubleshooting and performance optimization skills in SQL, Spark or other data engineering solutions
Experience operationalizing Generative AI (GenAI Ops) pipelines, including model deployment, monitoring, retraining, and lifecycle management for LLMs and AI-enabled data workflows