AI & Data Architecture Expert

aramco digital; Dhahran Compound; On-site; SAR 120,000 - 150,000; Full time

Job summary

A leading energy company in Dhahran seeks an AI & Data Architecture Expert to design robust data platforms. This role requires over 6 years of experience in data engineering and expertise in big data technologies and cloud services. You will define best practices and standards for data management while collaborating with multi-disciplinary teams to architect scalable solutions. Strong programming skills and hands-on experience with technologies like Hadoop and Spark are essential. Join us to shape the future of data-driven decision-making.

Qualifications

• 6+ years of experience in data engineering, software engineering, or ML engineering.
• 3+ years of experience architecting complex data and/or AI/ML platforms.
• Hands-on experience with big data technologies and cloud data services.
• Deep expertise in cloud-native data services and architecture.
• Experience with real-time data processing technologies.

Responsibilities

• Design end-to-end architectures for AI/ML and data platforms.
• Define standards for data management, governance, and MLOps.
• Evaluate technologies for data processing, storage, and analytics.
• Collaborate with teams to understand requirements.
• Ensure platform designs meet performance and security needs.
• Architect solutions for real-time data processing.
• Design data governance and metadata management solutions.
• Provide technical leadership on AI/data architecture matters.

Skills

Data modeling

Data warehousing concepts

Data pipeline orchestration

MLOps principles

Python

Scala

Java

Education

Bachelor’s degree in Computer Science, Engineering, Data Science, or related field

Master’s degree

Tools

Hadoop

Spark

AWS

Azure

GCP

Kafka

Kinesis

Job description

Overview:

We are looking for a forward-thinking AI & Data Architecture Expert to design and shape the future of our artificial intelligence and data platforms. You will be responsible for architecting scalable, robust, and efficient systems for data ingestion, processing, storage, machine learning model development, deployment, and analytics. Your expertise will be crucial in building the foundational platforms that enable data-driven decision-making and power intelligent features within our software products and operations.

Key Responsibilities:

• Design end-to-end architectures for AI/ML and data platforms, encompassing data pipelines, data lakes/warehouses, ML model training/serving infrastructure, and analytics environments.
• Define standards, patterns, and best practices for data management, data governance, MLOps, and AI model development.
• Evaluate and recommend technologies, frameworks, and tools for data processing (e.g., Spark, Flink), storage (e.g., S3, HDFS, NoSQL), ML platforms (e.g., SageMaker, Kubeflow, MLflow), and data warehousing/analytics (e.g., Snowflake, BigQuery, Redshift).
• Collaborate with data scientists, ML engineers, data engineers, and software developers to understand requirements and translate them into effective platform architectures.
• Ensure platform designs address scalability, performance, security, reliability, and costefficiency requirements.
• Architect solutions for real-time data processing and streaming analytics.
• Design data governance and metadata management solutions.
• Provide technical leadership and guidance on AI/data architecture matters.
• Stay abreast of the latest trends and advancements in AI, machine learning, and big data technologies.

Qualifications:

Education:

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (Master’s degree is preferred)

Experience:

• 6+ years of experience in data engineering, software engineering, or ML engineering.
• 3+ years of experience specifically architecting complex data and/or AI/ML platforms.
• Hands-on experience with big data technologies (e.g., Hadoop ecosystem, Spark), cloud data services (AWS/Azure/GCP), and ML frameworks/platforms.
• Deep expertise in cloud-native data services and architecture.
• Experience with real-time data processing technologies (e.g., Kafka, Kinesis).

Skills & Competencies:

• Strong understanding of data modeling, data warehousing concepts, data pipeline orchestration, and MLOps principles
• Strong programming skills (e.g., Python, Scala, Java).