Data Engineer | Senior Level | AI Infrastructure

Exciting Opportunity!About the company I am currently partnering with an established enterprise organization that leverages large-scale cloud data platforms and artificial intelligence to drive business intelligenceAbout JobYou will be focusing on the following: Architect and automate end-to-end data pipelines using modern orchestration tools to ensure highly reliable, self-healing data delivery. Optimize modern lakehouse and warehousing platforms to maximize query performance while minimizing infrastructure compute costs. Construct scalable data foundations for machine learning workloads, including feature stores, model registries, and automated retraining workflows. Integrate advanced monitoring, alerting, and automated quality checks to guarantee continuous system uptime and data trust. Collaborate closely with cross-functional product and analytics teams to turn business use cases into resilient engineering workflows. Streamline deployment processes by implementing containerized jobs, Infrastructure-as-Code, and automated CI/CD practices. Skills and RequirementsBachelor's or Master's degree in Computer Science, Information Systems, or a related technical discipline. At least 6 years of dedicated data engineering experience, specifically managing large-scale, multi-terabyte production datasets. Expert-level command of SQL and Python, alongside experience with distributed processing frameworks like Spark or Hadoop. Strong technical background with cloud-native environments, specifically AWS core ecosystems (such as Redshift, Glue, EMR, S3, and Athena). Hands-on exposure to modern data platforms and automation frameworks like Snowflake, Databricks, dbt, Airflow, or Prefect. Sound understanding of data security protocols, MLOps platforms, and regional compliance frameworks such as PDPA or GDPRTo apply online please use the 'apply' function, alternatively you may contact Evangeline.(EA: 94C3609/ R24124002 )