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data engineer

MASTER-WORKS

<div>Nationality: Any Arabic Nationality to achieve better communication and understand our Arabic data content better.
Data Engineer Roles and Responsibilities:
1. Data Collection and Integration: Data engineers collect data from various sources, including databases, APIs, external data providers, and streaming sources. They must design and implement efficient data pipelines to ensure a smooth flow of information into the data warehouse or storage system.
2. Data Storage and Management: Once the data is collected, data engineers are responsible for its storage and management. This involves choosing appropriate database systems, optimizing data schemas, and ensuring data quality and integrity. They also must consider scalability and performance to handle large volumes of data.
3. ETL (Extract, Transform, Load) Processes: ETL is a fundamental process in data engineering. Data engineers design ETL pipelines to transform raw data into a format suitable for analysis. This involves data cleansing, aggregation, and enrichment, ensuring the data is usable for data scientists and analysts.
4. Big Data Technologies: In today's data landscape, dealing with big data is the norm rather than the exception. Data engineers work with big data technologies such as Hadoop and Spark to efficiently process and analyze massive datasets.
5. NoSQL Databases: In addition to traditional relational databases, data engineers often work with NoSQL databases like MongoDB and Cassandra, which are well-suited for handling unstructured or semi-structured data.
6. Cloud Computing: Cloud platforms like AWS, Azure, and Google Cloud have become the backbone of modern data infrastructure. Data engineers leverage these platforms to build scalable and cost-effective data solutions.
7. Distributed Systems: Data engineering often involves distributed systems architecture to handle huge data volumes and ensure fault tolerance. Understanding how distributed systems work is essential for data engineers. 8. Streaming Data: Real-time data processing is crucial in many industries. Data engineers work with streaming technologies like Apache Kafka to handle and analyze data as it flows in 
 
 
Requirements 
Nationality: Any Arabic Nationality to achieve better communication and understand our Arabic data content better.
preferably 5+ years of experience.</div>

Data Engineer

<div>Master Works is hiring an experienced Data Engineer (5+ years) in Riyadh to design and optimize large-scale real-time and batch data pipelines within the Telecom domain.<ul><li>
Design, develop, and maintain real-time and batch data pipelines leveraging Kafka, Spark, and Hadoop components.</li><li>
Must have understanding of Teradata CLDM, should know how to create new Data Model or modify existing data model based on business requirement</li><li>
Collaborate with business analysts and data architects to translate business requirements into robust data models and ETL frameworks.</li><li>
Apply Relational and Dimensional modeling techniques to design databases and ensure data is organized effectively for both operational and analytical purposes.</li><li>
Write, debug, and optimize SQL and Stored Procedures to ensure efficient data processing.</li><li>
Work closely with BI, Data Science, and Campaign teams to ensure seamless data availability for analytics</li><li>
Work closely with Data Architects, Analysts, and Business Stakeholders to translate business requirements into database solutions.</li><li>
Ensure all database design and code is well-documented and follows best practices for performance and maintainability.</li><li>
Involves designing fact and dimension tables for reporting and analytics purposes, often in a star or snowflake schema.</li><li>
Develop and maintain technical documentation (data flow diagrams, source-to-target mappings, architecture documents).</li><li>
Ensure that the Data Dictionary is always up-to-date, capturing all changes to the database schema, including newly created or modified tables, columns, views,</li><li>
Perform data quality checks, validation, and ensure end-to-end data accuracy and lineage.</li><li>
Support and troubleshoot real-time streaming jobs and ensure high availability of data pipelines</li></ul> 
 
 
Requirements 
Have-Must<ul><li>
Strong expertise in real-time data integration using Kafka, Spark Streaming, or Dataflow.</li><li>
Hands-on experience with Hadoop ecosystem components (HDFS, Hive, Sqoop, Spark etc.).</li><li>
Strong Data Modeling concepts including FSLDM, CLDM, and Dimensional / Data Vault modeling.</li><li>
Deep understanding of Telecom domain (BSS/OSS, CDR, usage, revenue, and campaign data).</li><li>
Experience building and optimizing ETL pipelines and data ingestion frameworks for structured and unstructured data.</li><li>
Proficiency in SQL and distributed data processing using Hive, Spark SQL, or PySpark.</li><li>
Good understanding of data governance, data quality, and lineage frameworks.</li><li>
Strong analytical and problem-solving skills.</li><li>
Excellent communication and collaboration skills with cross-functional teams.</li><li>
Experience in working on data vartulization tools like (Tibco. Trino etc)</li></ul> 
Good-to-Have<ul><li>
Familiarity with Data Catalogs, Metadata Management, and NDMO data governance standards.</li><li>
Experience with Data Catalogue tools.</li><li>
Familiarity with CI/CD pipelines, Git.</li><li>
Knowledge of ETL orchestration tools like Airflow, NiFi</li></ul></div>

Data engineer

<div>Master-Works is looking for a talented Data Engineer - ETL to join our dynamic team. In this role, you will focus on designing, developing, and maintaining ETL processes that extract, transform, and load data from various sources into our data platforms. Your work will enable data accessibility for analytics and reporting, driving key business decisions.
Key Responsibilities:<ul>
<li>Design, develop, and implement robust ETL processes to ensure efficient data extraction, transformation, and loading.</li>
<li>Collaborate with data analysts and business stakeholders to gather data requirements and translate them into technical specifications.</li>
<li>Optimize ETL workflows for performance, scalability, and reliability.</li>
<li>Monitor ETL processes to proactively identify and resolve data quality issues.</li>
<li>Document ETL processes, data models, and architecture to ensure clear understanding and maintainability.</li>
<li>Stay updated on emerging data technologies and best practices to recommend improvements to existing systems.</li> 
</ul> 
 
Requirements 
<ul><li>
Experience with ETL tools such as Informatica, Talend, and SSIS
</li><li>Proficient in programming languages such as Python, Java, Scala, or other relevant languages
</li><li>Strong skills in SQL and programming
</li><li>Ability to optimize ETL performance
</li><li>Experience with data integration techniques and tools to design efficient and scalable data architectures
</li><li>6+ years of professional experience</li></ul></div>

Data Engineer - ETL

Muller's Solutions

<div>M&uuml;ller&rsquo;s Solutions is looking for an experienced Big Data Engineer to join our innovative team. In this role, you will be responsible for designing and developing scalable big data solutions that enable advanced analytics and insights across the organization. You will work with large data sets and utilize cutting-edge technologies to ensure data processing is efficient and reliable.
Key Responsibilities:<ul>
<li>Design, build, and maintain scalable data pipelines using big data technologies such as Apache Spark, Hadoop, and Kafka.</li>
<li>Collaborate with data scientists, analysts, and IT teams to identify data requirements and deliver solutions that meet business needs.</li>
<li>Ensure high data quality and integrity by implementing robust data validation and testing processes.</li>
<li>Optimize data storage solutions for performance and cost-efficiency across cloud and on-premises environments.</li>
<li>Monitor and troubleshoot data processing workflows to ensure timely data delivery.</li>
<li>Document data architectures, processes, and workflows for knowledge sharing and compliance.</li>
<li>Stay ahead of industry trends and best practices in big data technologies and methodologies.</li> 
</ul> 
 
Requirements 
Requirements:<ul>
<li>Bachelor's degree in Computer Science, Information Technology, or a related field.</li>
<li>3+ years of experience as a Big Data Engineer or in a similar data engineering role.</li>
<li>Proficiency in big data technologies such as Apache Spark, Hadoop, and Apache Kafka.</li>
<li>Strong coding skills in programming languages like Java, Scala, or Python.</li>
<li>Familiarity with data processing frameworks and ETL tools.</li>
<li>Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and data storage solutions (e.g., HDFS, S3, BigQuery).</li>
<li>Analytical mindset and excellent problem-solving abilities.</li>
<li>Strong communication skills to collaborate effectively with technical and non-technical stakeholders.</li>
<li>A self-motivated and proactive approach to work, with the ability to manage multiple tasks and deadlines.</li>
</ul>Preferred Qualifications:<ul>
<li>Experience with machine learning frameworks and algorithms is a plus.</li>
<li>Knowledge of data governance and security best practices.</li>
<li>Familiarity with containerization technologies and orchestration tools like Docker and Kubernetes.</li> 
</ul> 
 
Benefits 
1- Attractive Package.
2- Family Benefits.
3- Visa.
4-Air Tickets.</div>

Big Data Engineer

Master Works

<div>
 
 Master-Works is looking for a talented Data Engineer - ETL to join our dynamic team. In this role, you will focus on designing, developing, and maintaining ETL processes that extract, transform, and load data from various sources into our data platforms. Your work will enable data accessibility for analytics and reporting, driving key business decisions.
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Design, develop, and implement robust ETL processes to ensure efficient data extraction, transformation, and loading.
 </li>
 <li>
 Collaborate with data analysts and business stakeholders to gather data requirements and translate them into technical specifications.
 </li>
 <li>
 Optimize ETL workflows for performance, scalability, and reliability.
 </li>
 <li>
 Monitor ETL processes to proactively identify and resolve data quality issues.
 </li>
 <li>
 Document ETL processes, data models, and architecture to ensure clear understanding and maintainability.
 </li>
 <li>
 Stay updated on emerging data technologies and best practices to recommend improvements to existing systems.
 </li>
 
 
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Experience with ETL tools such as
 
 Informatica, Talend, and SSIS
 
 </li>
 <li>
 Proficient in programming languages such as
 
 Python, Java, Scala
 
 , or other relevant languages
 </li>
 <li>
 Strong skills in
 
 SQL and programming
 
 </li>
 <li>
 Ability to
 
 optimize ETL performance
 
 </li>
 <li>
 Experience with
 
 data integration techniques and tools
 
 to design
 
 efficient and scalable data architectures
 
 </li>
 <li>
 
 6+ years of professional experience
 
 </li>
 </ul>
</div>

<div>M&uuml;ller&rsquo;s Solutions is actively searching for a Google Cloud Data Engineer to enhance our data processing capabilities. In this vital role, you will be responsible for designing and implementing data pipelines leveraging Google Cloud technologies. You will work closely with data analysts, business stakeholders, and other engineering teams to ensure data is accurately processed, integrated, and made available for analysis and reporting. 
Key Responsibilities:<ul><li>
Design, develop, and optimize data pipelines using Google Cloud Dataflow, Pub/Sub, and other GCP data services.</li><li>
Implement data lakes and data warehouses using Google BigQuery, ensuring efficient data storage, retrieval, and processing.</li><li>
Collaborate with data scientists and analysts to understand data requirements and provide solutions that meet business needs.</li><li>
Monitor and evaluate data pipeline performance, implementing necessary optimizations and troubleshooting issues as they arise.</li><li>
Ensure data quality by developing and implementing validation routines and data profiling techniques.</li><li>
Document data architecture, ETL processes, and operational procedures to facilitate knowledge sharing within the team.</li><li>
Stay informed of emerging trends and best practices in data engineering and GCP technologies.</li><li>
Participate in team efforts to define and enhance data governance and management practices.</li></ul> 

Requirements 
Requirements:<ul>
<li>Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.</li>
<li>3+ years of experience in data engineering, with a focus on Google Cloud Platform.</li>
<li>Proficient in designing and implementing data pipelines using Google Cloud Dataflow, BigQuery, and related tools.</li>
<li>Strong SQL skills and experience in data modeling and data warehousing concepts.</li>
<li>Familiarity with programming languages such as Python or Java for data processing tasks.</li>
<li>Ability to work with various data sources, including structured and unstructured data.</li>
<li>Strong analytical and problem-solving skills with attention to detail.</li>
<li>Ability to effectively communicate technical concepts to both technical and non-technical stakeholders.</li>
</ul>Preferred Qualifications:<ul>
<li>Google Cloud certifications (e.g., Google Cloud Professional Data Engineer) are highly desirable.</li>
<li>Experience with real-time data processing using Apache Beam and Google Cloud Pub/Sub.</li>
<li>Understanding of CI/CD practices in data engineering workflows.</li>
<li>Knowledge of data visualization tools and techniques to present data insights effectively.</li> 
</ul> 
 
Benefits 
1- Attractive Package.
2- Family Benefits.
3- Visa.
4-Air Tickets.</div>

Google Cloud Data Engineer

Omnicom Media Group (MENA)

<div>
 
 
 Purpose:
 
 
 
 Maintain and oversee the client CDP composable architecture, ensuring seamless integration of Snowflake, Axciom, Hightouch, and Dataiku with client data sources and activation channels. Collaborate with other engineers and analysts during the Maintanance phase.The role demands active production level coding and scripting.
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 Architecture Design
 
 
 <ul>
 <li>
 Produce detailed integration blueprints for ingestion, identity resolution, enrichment, and activation.
 </li>
 <li>
 Define schema governance, metadata tagging, and golden record architecture.
 </li>
 </ul>
 
 
 Platform Enablement
 
 
 <ul>
 <li>
 Ensure Snowflake private/public marketplace integrations meet business requirements.
 </li>
 <li>
 Configure native app integrations (Hightouch, Axciom) for direct in-warehouse processing.
 </li>
 </ul>
 
 
 Scalability &amp; Modularity
 
 
 <ul>
 <li>
 Maintain modular design for future plug-and-play with new partners or channels.
 </li>
 <li>
 Optimize compute performance and storage costs via Snowflake elastic scaling.
 </li>
 </ul>
 
 
 Governance Integration
 
 
 <ul>
 <li>
 Embed RBAC, masking, and consent tagging into technical workflows.
 </li>
 </ul>
 
 
 Communication &amp; Documentation
 
 
 <ul>
 <li>
 Communicate clearly and professionaly with senior client stakeholders and cleint technical managers.
 </li>
 <li>
 Ensure documentation, standards, and best practices are enforced across the team.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Required Skills &amp; Experience
 
 
 <ul>
 <li>
 Strictly 4&ndash;7 years in data architecture/Engineering with proven
 
 Snowflake expertise
 
 .
 </li>
 <li>
 Deep knowledge of clean room integrations, composable CDP design, and reverse ETL.
 </li>
 <li>
 Experience with GCP( Big query, cloud run, load balancer etc) Informatica, dbt, Snowpipe, and marketplace data feeds.
 </li>
 <li>
 Familiarity with PDPL and SDAIA-aligned governance.
 </li>
 <li>
 
 Snowflake certification preferred
 
 (SnowPro Advanced Architect or equivalent).
 </li>
 <li>
 Strong written and verbal skills to articulate technical designs to non-technical stakeholders.
 </li>
 <li>
 Capability to balance immediate delivery with long-term scalability and modularity.
 </li>
 </ul>
 
 
 
 
 
 Education &amp; Qualification Requirements
 
 
 <ul>
 <li>
 
 Bachelor&rsquo;s degree in Computer Science, Data Engineering, Information Systems, or related field
 
 (mandatory).
 </li>
 <li>
 Professional certifications:
 </li>
 <li>
 
 Snowflake Certified Architect
 
 (strongly preferred).
 </li>
 <li>
 Certifications in
 
 Cloud Platforms
 
 (GCP desirable).
 </li>
 <li>
 
 Informatica or equivalent ETL tool certifications
 
 are an advantage.
 </li>
 <li>
 
 DBT proficiencey with Medallion architecture.
 
 </li>
 </ul>
 
 
</div>

Senior Data Engineer - Snowflake & GCP

Explore 1406+ Data engineer in Saudi Arabia this March. Find roles across top companies and apply now to boost your career.

1406 data engineer jobs In Saudi Arabia

Data Engineer

Data engineer

Data Engineer - ETL

Big Data Engineer

Data Engineer - ETL

Google Cloud Data Engineer

Senior Data Engineer - Snowflake & GCP