17 Etl Processes jobs in Saudi Arabia

• 8+ years of experience in data engineering with at least 2–3 years in a managerial or lead capacity
• Strong experience with SQL, Python/Scala, and data architecture patterns in financial systems
• Hands-on experience with data platforms such as Hadoop, Spark, Snowflake, Redshift, or BigQuery
• Experience with banking core systems (e.g., Temenos, Finacle, FIS) and financial data integration is a strong advantage
• Familiarity with financial regulations and reporting standards (e.g., BCBS 239, MiFID II, GDPR)

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field
• Certified Data Management Professional (CDMP)
• AWS/GCP/Azure Data Engineer Certifications

• Winner of Entrepreneur 360 Award (2019).
• IAOP Award; Ranked in 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.

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

• 8+ years of experience in data engineering with at least 2–3 years in a managerial or lead capacity
• Strong experience with SQL, Python/Scala, and data architecture patterns in financial systems
• Hands-on experience with data platforms such as Hadoop, Spark, Snowflake, Redshift, or BigQuery
• Experience with banking core systems (e.g., Temenos, Finacle, FIS) and financial data integration is a strong advantage
• Familiarity with financial regulations and reporting standards (e.g., BCBS 239, MiFID II, GDPR)

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field
• Certified Data Management Professional (CDMP)
• AWS/GCP/Azure Data Engineer Certifications

• Winner of Entrepreneur 360 Award (2019).
• IAOP Award; Ranked in 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.

Qiddiya Investment Company is looking for a skilled and innovative Senior Specialist - Data Engineer to join our technology team. As a Senior Data Engineer, you will use various methods to transform raw data into useful data systems. Collaborate closely with cross-functional teams to ensure the availability, reliability, and accessibility of data for analytics and decision-making purposes. Overall, you’ll strive for efficiency by aligning data systems with business goals. To succeed in this data engineering position, you should have strong analytical skills and the ability to combine data from different sources. Data engineer skills also include familiarity with several programming languages and knowledge of learning machine methods

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL processes using tools such as Apache Spark, Apache Kafka, and Apache Airflow to ingest, process, and transform large volumes of data from various sources.
• Deploy Data Pipeline on different Data Processing Product - DataFlow (Apache Beam), DataProc (Hadoop / Spark), Data Fusion, Composer(Airflow)
• Building distributed systems and data stores
• Collaborating with and supporting data science, marketing, and customer success teams in data acquisition and tool integration
• Configuration of Google Cloud Platform services
• Implement and optimize data storage solutions, including data warehouses (e.g., Amazon Redshift, Google BigQuery), data lakes (e.g., AWS S3, Azure Data Lake Storage), and NoSQL databases (e.g., MongoDB, Cassandra).
• Work closely with data architects to design and implement efficient data models using dimensional modeling techniques (e.g., star schema, snowflake schema) that support business requirements and enable effective data analysis.
• Collaborate with data scientists and analysts to understand data requirements and develop solutions to support advanced analytics and machine learning initiatives, including model training and deployment.
• Implement data quality checks, monitoring and custom scripts to ensure the accuracy, completeness, and reliability of data.
• Participate in troubleshooting and resolving data-related issues, ensuring timely resolution and minimal disruption to business operations.
• Stay updated on emerging technologies and best practices in data engineering, including cloud native solutions and serverless architectures, and contribute to the continuous improvement of data platforms and infrastructure.
• Solid knowledge of Google’s BigQuery for effective data processing
• Proposing and implementing repetitive tasks automation.
• Providing support for development teams in deployment-related topics.
• Modernizing data lakes and data warehouses

Requirements

Qiddiya Investment Company is looking for a skilled and innovative Senior Specialist - Data Engineer to join our technology team. As a Senior Data Engineer, you will use various methods to transform raw data into useful data systems. Collaborate closely with cross-functional teams to ensure the availability, reliability, and accessibility of data for analytics and decision-making purposes. Overall, you’ll strive for efficiency by aligning data systems with business goals. To succeed in this data engineering position, you should have strong analytical skills and the ability to combine data from different sources. Data engineer skills also include familiarity with several programming languages and knowledge of learning machine methods

• Design, develop, and maintain scalable data pipelines and ETL processes using tools such as Apache Spark, Apache Kafka, and Apache Airflow to ingest, process, and transform large volumes of data from various sources.
• Deploy Data Pipeline on different Data Processing Product - DataFlow (Apache Beam), DataProc (Hadoop/Spark), Data Fusion, Composer(Airflow)
• Building distributed systems and data stores
• Collaborating with and supporting data science, marketing, and customer success teams in data acquisition and tool integration
• Configuration of Google Cloud Platform services
• Implement and optimize data storage solutions, including data warehouses (e.g., Amazon Redshift, Google BigQuery), data lakes (e.g., AWS S3, Azure Data Lake Storage), and NoSQL databases (e.g., MongoDB, Cassandra).
• Work closely with data architects to design and implement efficient data models using dimensional modeling techniques (e.g., star schema, snowflake schema) that support business requirements and enable effective data analysis.
• Collaborate with data scientists and analysts to understand data requirements and develop solutions to support advanced analytics and machine learning initiatives, including model training and deployment.
• Implement data quality checks, monitoring and custom scripts to ensure the accuracy, completeness, and reliability of data.
• Participate in troubleshooting and resolving data-related issues, ensuring timely resolution and minimal disruption to business operations.
• Stay updated on emerging technologies and best practices in data engineering, including cloud native solutions and serverless architectures, and contribute to the continuous improvement of data platforms and infrastructure.
• Solid knowledge of Google’s BigQuery for effective data processing
• Proposing and implementing repetitive tasks automation.
• Providing support for development teams in deployment-related topics.
• Modernizing data lakes and data warehouses

• 3 - 6 of years of experience as a data engineer or in a similar role.
• Technical expertise with data models, data mining, and segmentation techniques.
• Proficiency in programming languages such as Python, Java, or Scala, and experience with SQL and NoSQL databases.
• Strong understanding of data modeling, ETL processes, data warehousing concepts, and data integration techniques.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform, and familiarity with related services (e.g., AWS Glue, Azure Data Factory, Google BigQuery).
• Excellent problem-solving skills and attention to detail, with the ability to work effectively in a fast-paced environment and manage multiple priorities.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and stakeholders.
• Degree in Computer Science, IT, or similar field; a Master’s is a plus.
• Data engineering cloud certification (e.g Google Certified Data Engineer) is a plus

Qiddiya Investment Company is looking for a skilled and innovative Senior Specialist - Data Engineer to join our technology team. As a Senior Data Engineer, you will use various methods to transform raw data into useful data systems. Collaborate closely with cross-functional teams to ensure the availability, reliability, and accessibility of data for analytics and decision-making purposes. Overall, you’ll strive for efficiency by aligning data systems with business goals. To succeed in this data engineering position, you should have strong analytical skills and the ability to combine data from different sources. Data engineer skills also include familiarity with several programming languages and knowledge of learning machine methods

• Design, develop, and maintain scalable data pipelines and ETL processes using tools such as Apache Spark, Apache Kafka, and Apache Airflow to ingest, process, and transform large volumes of data from various sources.
• Deploy Data Pipeline on different Data Processing Product - DataFlow (Apache Beam), DataProc (Hadoop/Spark), Data Fusion, Composer(Airflow)
• Building distributed systems and data stores
• Collaborating with and supporting data science, marketing, and customer success teams in data acquisition and tool integration
• Configuration of Google Cloud Platform services
• Implement and optimize data storage solutions, including data warehouses (e.g., Amazon Redshift, Google BigQuery), data lakes (e.g., AWS S3, Azure Data Lake Storage), and NoSQL databases (e.g., MongoDB, Cassandra).
• Work closely with data architects to design and implement efficient data models using dimensional modeling techniques (e.g., star schema, snowflake schema) that support business requirements and enable effective data analysis.
• Collaborate with data scientists and analysts to understand data requirements and develop solutions to support advanced analytics and machine learning initiatives, including model training and deployment.
• Implement data quality checks, monitoring and custom scripts to ensure the accuracy, completeness, and reliability of data.
• Participate in troubleshooting and resolving data-related issues, ensuring timely resolution and minimal disruption to business operations.
• Stay updated on emerging technologies and best practices in data engineering, including cloud native solutions and serverless architectures, and contribute to the continuous improvement of data platforms and infrastructure.
• Solid knowledge of Google’s BigQuery for effective data processing
• Proposing and implementing repetitive tasks automation.
• Providing support for development teams in deployment-related topics.
• Modernizing data lakes and data warehouses

• 3 - 6 of years of experience as a data engineer or in a similar role.
• Technical expertise with data models, data mining, and segmentation techniques.
• Proficiency in programming languages such as Python, Java, or Scala, and experience with SQL and NoSQL databases.
• Strong understanding of data modeling, ETL processes, data warehousing concepts, and data integration techniques.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform, and familiarity with related services (e.g., AWS Glue, Azure Data Factory, Google BigQuery).
• Excellent problem-solving skills and attention to detail, with the ability to work effectively in a fast-paced environment and manage multiple priorities.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and stakeholders.
• Degree in Computer Science, IT, or similar field; a Master’s is a plus.
• Data engineering cloud certification (e.g Google Certified Data Engineer) is a plus

As a SA/VLM associate, you will be responsible for creating high-quality written content for videos/images and/or labeling of objects on audio, image, and/or video-file. Your primary focus will be on producing clear, concise, and informative content that meets the needs of the target audience.


Key job responsibilities
• Performs simple annotation-related tasks in a narrow ML data process area (e.g. audio, image, and/or video-file). Uses internal tools and software provided by team.
• May participate in data collection activities when scripts and instructions are provided. Adheres to compliance and confidentiality requirements.
• Apply strong language skills, grammar knowledge, and linguistic rules to ensure the generated text adheres to proper grammar, syntax, and appropriate language usage.
• Maintaining high internal quality of the processes by performing quality audits/verification.
• Meets daily productivity and quality targets. Tracks queries related to annotation/data collection and share them with the relevant stakeholders to help solve them.
• Track daily task completion status using recommended tools and provide individual status reports.
• Adhere to confidentiality & compliance requirements to ensure zero risk to customer data and Amazon. Helps test new SOPs and ML data tools.
• Providing specific & timely feedback to streamline existing processes and help the team achieve more consistent results with high quality.
• Offering remedial instruction in tool usage and other topics as required.
Requirements:
• Strong command of the English language, including grammar, syntax, and vocabulary.
• Background in linguistics, creative writing, computational linguistics, or a related field is preferred.
• Analytical mindset with the ability to evaluate and interpret data to improve the performance of the system.
• Good familiarity with the Windows desktop environment and uses of Word, Excel, IE, Firefox etc. are required
• Flexibility and Interest to do repetitive tasks is required.
• High level of energy and proactive nature. A sense of ownership and drive and a willingness to accept the challenge of daily deadlines is essential
• Attention to detail and ability to identify and rectify errors or inconsistencies in descriptions generated.
• Strong problem-solving skills and the ability to work effectively in a fast-paced, collaborative environment.
• Passion for language, technology, and AI advancements.
• Ability to meet deadlines, prioritize tasks, and manage multiple projects simultaneously.

- Bachelor's degree
- Speak, write, and read fluently in English
- Knowledge of Microsoft Office products and applications
- Work a flexible schedule/shift/work area, including weekends, nights, and/or holidays
- Certification in any of the following: Content Writing, Creative Writing, English Literature, English, Literary Arts, Linguistics, English as a Second Language Teaching (preferred).

- Bachelor's degree in English, Journalism, Marketing, or a related field (preferred).
- Prior experience of 2-4 years and familiarity with US culture preferred; or experience in multicultural communication will be a plus.

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