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Urgent! Senior Data Engineer – AI Data Platform (OCI Lakehouse) Job Opening In Mexico, Mexico – Now Hiring Oracle

Senior Data Engineer – AI Data Platform (OCI Lakehouse)



Job description

What You’ll Be Doing (Core Mission)

  • Design and implement large-scale, fault-tolerant data pipelines on OCI, using services like OCI Data Integration, OCI Data Flow (Apache Spark), Object Storage, and Autonomous Database.
  • Build and manage streaming data architectures using tools such as OCI GoldenGate, Apache Kafka, and Spark/Flink Streaming.
  • Enforce standards and automation across the entire data lifecycle, including schema evolution, dataset migration, and deprecation strategies.
  • Improve platform resilience, data quality, and observability with advanced monitoring, alerting, and automated data governance.
  • Serve as a technical leader, mentoring junior engineers, reviewing designs and code, and promoting engineering best practices.
  • Collaborate cross-functionally with ML engineers, platform teams, and data scientists to integrate data services with AI/ML workloads.
  • Partner in AI pipeline enablement, ensuring Lakehouse services efficiently support model training, feature engineering, and real-time inference.
  • Required Technical Skills & Experience


     Engineering & Infrastructure

  • 5+ years building distributed systems or production-grade data platforms in the cloud.
  • Strong coding proficiency in Python, Java, or Scala, with an emphasis on performance and reliability.
  • Expertise in SQL and PLSQL, data modeling, and query optimization.
  • Proven experience with cloud-native architectures—especially OCI, AWS, Azure, or GCP.
  •  Lakehouse & Streaming Mastery

  • Deep knowledge of modern lakehouse/table formats: Apache Iceberg, Delta Lake, or Apache Hudi.
  • Production experience with big data compute engines: Spark, Flink, or Trino.
  • Skilled in real-time streaming and event-driven architectures using Kafka, Flink, GoldenGate, or Streaming.
  • Experience managing data lakes, catalogs, and metadata governance in large-scale environments.
  •  AI/ML Integration

  • Hands-on experience enabling ML pipelines: from data ingestion to model training and deployment.
  • Familiarity with ML frameworks (., PyTorch, XGBoost, scikit-learn).
  • Understanding of modern ML architectures: including RAG, prompt chaining, and agent-based workflows.
  • Awareness of MLOps practices, including model versioning, feature stores, and integration with AI pipelines.
  • DevOps & Operational Excellence

  • Deep understanding of CI/CD, infrastructure-as-code (IaC), and release automation using tools like Terraform, GitHub Actions, or CloudFormation.
  • Experience with Docker, Kubernetes, and cloud-native container orchestration.
  • Strong focus on testing, documentation, and system observability (Prometheus, Grafana, ELK stack).
  • Comfortable with cost/performance tuning, incident response, and data security standards (IAM, encryption, auditing).
  • Preferred Qualifications

  • Experience with Oracle’s cloud-native tools: OCI Data Integration, Data Flow, Autonomous Database, GoldenGate, OCI Streaming.
  • Experience with query engines like Trino or Presto, and tools like dbt or Apache Airflow.
  • Familiarity with data cataloging, RBAC/ABAC, and enterprise data governance frameworks.
  • Exposure to vector databases and LLM tooling (embeddings, vector search, prompt orchestration).
  • Solid understanding of data warehouse design principles, star/snowflake schemas, and ETL optimization.
  • Minimum Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical field.
  • 4–6 year’s experience designing and building cloud-based data pipelines and distributed systems.
  • Proficiency in at least one core language: Python, Java, or Scala.
  • Familiar with lakehouse formats (Iceberg, Delta, Hudi), file formats (Parquet, ORC, Avro), and streaming platforms (Kafka, Kinesis).
  • Strong understanding of distributed systems fundamentals: partitioning, replication, idempotency, consensus protocols.
  • Soft Skills & Team Expectations

  • Proven ability to lead technical initiatives independently end-to-end.
  • Comfortable working in cross-functional teams and mentoring junior engineers.
  • Excellent problem-solving skills, design thinking, and attention to operational excellence.
  • Passion for learning emerging data and AI technologies and sharing knowledge across teams.
  • Career Level - IC3


    Required Skill Profession

    Computer Occupations



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