170 Big Data Technologies jobs in Saudi Arabia

Overview

Data Engineering Specialist role at Takamol Holding.

Design, build, and manage scalable data pipelines to collect, transform, and store data from various internal and external sources.

Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements. Ensure data integrity, accuracy, and availability across all systems and platforms. Optimize data infrastructure for performance, reliability, and cost-efficiency. Develop and maintain processes using modern data tools and platforms. Implement data governance, security, and privacy best practices in compliance with regulatory requirements. Monitor, troubleshoot, and improve data workflows and performance issues. Document data architecture, data flows, and technical processes. Support the development of data models and analytical datasets for reporting and AI/ML use cases.

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
• 2–5 years of experience in data engineering, data warehousing, or similar roles.
• Strong problem-solving and communication skills.
• Analytical Thinking
• Leadership
• Teamwork and Time Management

• Entry level

• Full-time

• Engineering and Information Technology

• Business Consulting and Services

Arthur Lawrence is urgently looking for a Manager - Data Engineering for a client in Riyadh, KSA. Kindly review the job requirements below. Your immediate application will enable us to place you successfully.

• Minimum 10 years of proven experience in data management within the banking sector
• Skilled in big data technologies like Hadoop, Spark, Kafka, Impala, Nifi, and Hive
• Proficiency in implementing data governance policies, developing data processing and storage solutions
• Must be fluent in Arabic and English

• Bachelor’s degree in computer science, IT, or equivalent

• Winner of Entrepreneur 360 Award (2019)
• IAOP Award; Ranked in the top 100 internationally
• Arthur Lawrence ranked within the Inc 5000 twice in 2016 and 2017 as one of the fastest-growing companies in America
• Named one of the top ten fastest-growing businesses in Houston in 2016
• Ranked 25th in the HBJ's Fast 100 Private Companies Award in 2017

Job Purpose :

• The Manager of Data Engineering & Storage will help lead the design, development, and optimization of data pipelines, integration strategies, and storage infrastructure to support the Insurance Authority's data-driven objectives. The role ensures that data is ingested, processed, and stored securely and efficiently to serve analytical, operational, and regulatory needs.

Key Responsibilities and Activities

Operations Management:

Implement the policies, regulations, procedures, and controls so that all relevant procedural/ legislative requirements are met while delivering high-quality and cost-effective results.

Data Engineering & Storage :

Data Pipeline & Storage Development

• Design and optimize scalable data pipelines for real-time and batch processing.
• Ensure seamless data ingestion, transformation, and delivery from internal and external sources.
• Enhance automation and monitoring capabilities to reduce disruptions and optimize performance.
• Support regulatory data processing requirements and business analytics workflows.

Data Integration and Sharing

• Develop and implement data integration strategies for unifying data across systems and departments.
• Standardize data interoperability through APIs and common formats.
• Manage secure data-sharing processes within IA and with external stakeholders.
• Monitor integration workflows to ensure high performance and compliance.

Data Operations Management

• Oversee daily operations of data systems ensuring high availability and reliability.
• Monitor and report on Insurance Data Hub usage and performance.
• Define and manage access controls, backup, and disaster recovery for the Data Hub.
• Identify and resolve operational issues within data services to minimize service interruptions.
• Drive automation and process standardization to improve efficiency.

Data Architecture and Modelling

• Design and maintain scalable data architectures aligned with IA's data strategy.
• Build and evolve data models to support current and future data requirements.
• Collaborate with internal teams to align data models with business and analytical needs.
• Coordinate with the Data Quality & Monitoring team to enforce standards and ensure data integrity.

Storage Infrastructure Management

• Manage structured and unstructured data storage systems for optimal performance and reliability.
• Collaborate with IT Infrastructure & Operations for hybrid (cloud and on-premises) storage solutions.
• Implement and regularly test backup, rollback, and recovery mechanisms.
• Support Business Continuity by aligning data storage with disaster recovery strategies.

Security & Compliance Integration

• Enforce data security protocols in coordination with Cybersecurity teams.
• Ensure compliance with internal data governance and external regulatory requirements.
• Acquire and manage compliance-related data for monitoring regulatory adherence.
• Collaborate with Insight Generation & Decision Support teams to evaluate and improve compliance outcomes.
• Perform other activities as and when required.

Qualifications and Requirements

Knowledge and Experience :

• 8+ years or more of relevant experience in data engineering, integration, and infrastructure management or any relevant field.
• Previous experience in in data pipeline tools (e.g., Apache Airflow, Talend), storage platforms (e.g., Hadoop, cloud data lakes), and integration technologies (e.g., APIs, ETL frameworks).
• Strong understanding of data governance, security, and regulatory compliance.
• Experience working with hybrid environments (cloud and on-premises).
• Familiarity with disaster recovery, data privacy standards, and metadata management.

Education and Certifications:

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field.
• Relevant certification is preferred

About Mozn
Mozn is a rapidly growing technology firm revolutionising the field of Artificial Intelligence and Data Science headquartered in Riyadh, Saudi Arabia and it's working to realise Vision 2030 with a proven track record of excellence in supporting and growing the tech ecosystem in Saudi Arabia and the GCC region. Mozn is the trusted AI technology partner for some of the largest government organisations, as well as many large corporations and startups.

We are in an exciting stage of scaling the company to provide AI-powered products and solutions both locally and globally that ensure the growth and prosperity of our digital humanity. It is an exciting time to work in the field of AI to create a long-lasting impact.

About The Role
We are seeking a
*Data Science Manager *
to join our team. In this leadership role, you will be responsible for guiding and developing a team of data scientists, driving the full lifecycle of model development, and ensuring delivery of high-quality, client-focused solutions across a range of business domains. You'll work closely with internal teams and external clients, leading initiatives that encompass a broad spectrum of data science applications.

What You'll Do

• Lead and mentor a team of data scientists, overseeing all aspects of model development, evaluation, and deployment.
• Own the data science project lifecycle—from ideation and experimentation to prototyping, productionization, and monitoring—ensuring delivery of impactful client solutions.
• Collaborate with engineering, product teams, and clients to understand requirements, translate business problems into data-driven solutions, and communicate results.
• Contribute to the design and improvement of data and software platforms, emphasizing scalable, reusable, and service-oriented solutions.
• Keep the team up to date with emerging technologies and industry trends in data science, machine learning, and AI, supporting continuous learning and innovation.
• Support business development efforts by engaging in client discussions, understanding client needs, and proposing data science solutions tailored to diverse domains.
• Foster an inclusive, collaborative, and high-performance team culture, focused on excellence and client satisfaction.
• Attract, develop, and retain top data science talent.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• 6+ years of relevant experience, with at least 4 years in data science leadership or management roles.
• Proven experience developing and deploying data science solutions in production environments.
• Broad knowledge of machine learning, statistical modeling, and data analysis.
• Proficiency in Python and experience with frameworks such as PyTorch or TensorFlow.
• Experience working with large, real-world datasets (structured and unstructured).
• Familiarity with scalable ML infrastructure, cloud computing, and distributed computing is a plus.
• Strong client-facing communication skills; ability to translate technical concepts for business stakeholders.
• Proficiency in Arabic is preferred.
• Demonstrated ownership, collaboration, and commitment to excellence.

Benefits
*Why Mozn? *

• You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space.
• You will be given a lot of responsibility and trust. We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best.
• The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best.
• You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI.
• We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves.

Company Description

is a Saudi-based company at the forefront of the healthcare technology sector, specializing in advanced artificial intelligence. Our mission is to revolutionize healthcare by transforming standard Hospital Information Systems (HIS) and Electronic Health Records (EHR) into dynamic, intelligent systems. We provide real-time, evidence-based clinical support to align with the healthcare goals of Saudi Arabia's Vision 2030, enhancing patient outcomes and supporting medical professionals.

Role Description

This is a full-time online role for a Data Science Specialist located in Jeddah. The Data Science Specialist will be responsible for analyzing large datasets, developing statistical models, conducting data analysis, and utilizing data science techniques to extract insights. Day-to-day tasks include data analytics, developing data-driven solutions to improve patient outcomes, and collaborating with cross-functional teams to implement AI-driven healthcare solutions.

Qualifications

• Analytical Skills and Data Analysis skills
• Expertise in Data Science and Data Analytics
• Strong Statistics knowledge
• Proficient in programming languages such as Python or R
• Experience with machine learning algorithms and data visualization tools
• Excellent problem-solving and communication skills
• Ability to work collaboratively in a team environment
• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or related field
• Experience in the healthcare industry is a plus

Job Title

Sr. Engineer, Data Engineering

Section Head, Digitalization Infrastructure

Business Improvement

Operational Excellence

NA

M10

Job Family: Data Engineering

Sub Family: -

Engineer

-

The Sr. Engineer, Data Engineering applies strong expertise in developing, maintaining, and testing robust data infrastructures specifically for its operations. This role is critical for transforming raw operational data into a clean, accessible, and easily analyzable format, and for architecting scalable data solutions that empower data scientists and business stakeholders to derive insights and drive digitalization initiatives within the unit.

Data Architecture Development & Maintenance (Operational Focus):

• Develop, construct, test, and maintain data architectures, including databases and large-scale processing systems, specifically tailored for the unique data requirements of operational units.
• Ensure the data architecture will robustly support the requirements of data scientists, key stakeholders, and the business objectives for digitalization.
• Develop and improve data set processes for data modeling, data mining, and production environments within the operational context.

Data Reliability, Efficiency & Quality:

• Implement and continuously improve methods to enhance data reliability, efficiency, and quality across all data pipelines.
• Assist with data-related technical issues and provide essential support for data infrastructure needs specific to operational units.

Data Tooling & Enablement:

• Create and optimize data tools for analytics and data scientist team members that assist them in building and optimizing products crucial for achieving business goals and digitalization targets.
• Drive the adoption of best practices in data engineering to support advanced analytics and AI/ML initiatives.

Collaboration & Integration:

• Collaborate closely with the Digitalization - Infrastructure team to ensure seamless integration of data solutions within the broader digital infrastructure.
• Work with data scientists and operational teams to understand data needs and deliver effective data solutions.

Minimum Qualifications:

BSc/MSc in Computer Science, Information Systems or related Technical Discipline

Minimum Experience:

5-7 years of experience in manufacturing industry

Skills:

Deep knowledge of SQL, “Big data” data pipelines, architectures, and data sets, Experience working in AI start-up environment or organizations with an agile culture, Background in programming in Python, Scala, C etc. is beneficial

Trending

• Job Identification 5969
• Locations Turayf, Turayf, 11411, SA
• Job Schedule Full time

JobTitle

Sr. Engineer, Data Engineering

Reportingto

Section Head, Digitalization Infrastructure

Business Unit/Function

Business Improvement

Department

Operational Excellence

Direct Reports

NA

Budget/Size

Grade

M10

Job Family

Position Type

Engineer

Role Profile Number

Job Purpose

The Sr. Engineer, Data Engineering applies strong expertise in developing, maintaining, and testing robust data infrastructures specifically for its operations. This role is critical for transforming raw operational data into a clean, accessible, and easily analyzable format, and for architecting scalable data solutions that empower data scientists and business stakeholders to derive insights and drive digitalization initiatives within the unit.

Key Accountabilities

Data Architecture Development & Maintenance (Operational Focus):

• Develop, construct, test, and maintain data architectures, including databases and large-scale processing systems, specifically tailored for the unique data requirements of operational units.
• Ensure the data architecture will robustly support the requirements of data scientists, key stakeholders, and the business objectives for digitalization.
• Develop and improve data set processes for data modeling, data mining, and production environments within the operational context.
• Implement and continuously improve methods to enhance data reliability, efficiency, and quality across all data pipelines.
• Assist with data-related technical issues and provide essential support for data infrastructure needs specific to operational units.

Data Tooling & Enablement:

• Create and optimize data tools for analytics and data scientist team members that assist them in building and optimizing products crucial for achieving business goals and digitalization targets.
• Drive the adoption of best practices in data engineering to support advanced analytics and AI/ML initiatives.
• Collaborate closely with the Digitalization - Infrastructure team to ensure seamless integration of data solutions within the broader digital infrastructure.
• Work with data scientists and operational teams to understand data needs and deliver effective data solutions.

Minimum Qualifications, Experience and Competencies

Minimum Qualifications:

BSc/MSc in Computer Science, Computer Science, Information Systems or related Technical Discipline

Minimum Experience: 5-7 years of experience in manufacturing industry

Skills:

Deep knowledge of SQL, “Big data” data pipelines, architectures, and data sets, Experience working in AI start-up environment or organizations with an agile culture, Background in programming in Python, Scala, C etc. is beneficial

Trending

• Job Identification 5969
• Locations Turayf, Turayf, 11411, SA
• Job Schedule Full time

JobTitle

Sr. Engineer, Data Engineering

Reportingto

Section Head, Digitalization Infrastructure

Business Unit/Function

Business Improvement

Department

Operational Excellence

Direct Reports

NA

Budget/Size

Grade

M10

Job Family

Position Type

Engineer

Role Profile Number

Job Purpose

The Sr. Engineer, Data Engineering applies strong expertise in developing, maintaining, and testing robust data infrastructures specifically for its operations. This role is critical for transforming raw operational data into a clean, accessible, and easily analyzable format, and for architecting scalable data solutions that empower data scientists and business stakeholders to derive insights and drive digitalization initiatives within the unit.

Key Accountabilities

Data Architecture Development & Maintenance (Operational Focus):

• Develop, construct, test, and maintain data architectures, including databases and large-scale processing systems, specifically tailored for the unique data requirements of operational units.
• Ensure the data architecture will robustly support the requirements of data scientists, key stakeholders, and the business objectives for digitalization.
• Develop and improve data set processes for data modeling, data mining, and production environments within the operational context.
• Implement and continuously improve methods to enhance data reliability, efficiency, and quality across all data pipelines.
• Assist with data-related technical issues and provide essential support for data infrastructure needs specific to operational units.

Data Tooling & Enablement:

• Create and optimize data tools for analytics and data scientist team members that assist them in building and optimizing products crucial for achieving business goals and digitalization targets.
• Drive the adoption of best practices in data engineering to support advanced analytics and AI/ML initiatives.
• Collaborate closely with the Digitalization - Infrastructure team to ensure seamless integration of data solutions within the broader digital infrastructure.
• Work with data scientists and operational teams to understand data needs and deliver effective data solutions.

Minimum Qualifications, Experience and Competencies

Minimum Qualifications:

BSc/MSc in Computer Science, Computer Science, Information Systems or related Technical Discipline

Minimum Experience: 5-7 years of experience in manufacturing industry

Skills:

Deep knowledge of SQL, “Big data” data pipelines, architectures, and data sets, Experience working in AI start-up environment or organizations with an agile culture, Background in programming in Python, Scala, C etc. is beneficial