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Datamatics
Posted 1mo ago

Data Engineering & Warehousing Engineer

Datamatics
datamatics.comView all open roles
Riyadh, Riyadh, Saudi Arabia
OnsiteFull Time
Responsibilities
  • designing pipelines
  • building warehouses
  • integrating data
Requirements
  • 3+ years experience designing and maintaining ETL/ELT pipelines
  • Data warehouses and lakes
  • Strong SQL and Python skills
  • Experience with cloud data platforms and big data processing
Technical tools mentioned
Google BigQueryDataflowDataprocPub/SubAzure SynapseAzure Data FactoryAmazon RedshiftAWS GlueApache SparkApache KafkadbtOracle Data Integrator (ODI)OraclePostgreSQLSQLPythonGoogle Cloud PlatformMicrosoft AzureAmazon Web ServicesDockerKubernetes

Job description

Job Description: Data Engineering & Warehousing Engineer

Job Title: Data Engineering & Warehousing Engineer
Experience: 3–11 Years
Location: Riyadh - Onsite
Employment Type: Full-Time

Job Overview

We are seeking a highly skilled Data Engineering & Warehousing Engineer with 3–11 years of experience to design, develop, and maintain scalable data platforms and enterprise data warehouse solutions. The ideal candidate will have hands-on expertise in building ETL/ELT pipelines, data integration, cloud-based data platforms, and big data processing technologies. You will play a key role in enabling reliable, high-performance analytics and business intelligence solutions.

Key Responsibilities

  • Design, develop, and optimize scalable ETL/ELT pipelines for structured and unstructured data.
  • Build and maintain enterprise data warehouses, data lakes, and modern data platforms.
  • Develop real-time and batch data processing solutions.
  • Integrate data from multiple internal and external sources while ensuring data quality and governance.
  • Collaborate with Data Scientists, BI Developers, and business stakeholders to support analytical requirements.
  • Optimize data storage, query performance, and pipeline reliability.
  • Implement data security, monitoring, and governance best practices.
  • Troubleshoot and resolve data pipeline and platform issues.
  • Participate in architecture discussions and contribute to data platform modernization initiatives.

Required Technical Skills

Cloud Data Platforms

  • Hands-on experience with Google BigQuery and Dataflow and Dataproc and Pub/Sub.
  • Experience with Azure Synapse and Azure Data Factory.
  • Experience with Amazon Redshift and AWS Glue.

Data Processing & Streaming

  • Strong experience with Apache Spark and Apache Kafka.
  • Experience building batch and real-time data processing pipelines.

Data Transformation

  • Hands-on experience with dbt or Oracle Data Integrator (ODI) for data transformation and orchestration.
  • Experience implementing ETL/ELT best practices and reusable data models.

Databases & Data Warehousing

  • Strong experience with Oracle or PostgreSQL.
  • Expertise in SQL, relational database design, performance tuning, and query optimization.

Data Engineering

  • Experience with data modeling, data governance, metadata management, and data quality frameworks.
  • Knowledge of dimensional modeling and modern data warehouse architectures.

Qualifications

  • Bachelor's degree in Computer Science, Information Technology, Data Engineering, Software Engineering, or a related field.
  • 3–11 years of professional experience in Data Engineering, Data Warehousing, or Big Data technologies.
  • Strong programming and scripting skills using SQL, Python, or similar languages.
  • Excellent analytical and problem-solving abilities.
  • Experience working in Agile/Scrum development environments.

Preferred Skills

  • Experience with cloud-native data lake and lakehouse architectures.
  • Knowledge of CI/CD pipelines and Infrastructure as Code (IaC).
  • Familiarity with containerization technologies such as Docker and Kubernetes.
  • Experience supporting machine learning and analytics workloads.
  • Cloud certifications on AWS, Microsoft Azure, or Google Cloud Platform are a plus.

Key Technology Stack

  • Google Cloud Data Services: BigQuery and Dataflow and Dataproc and Pub/Sub
  • Azure Data Services: Azure Synapse and Azure Data Factory
  • AWS Data Services: Amazon Redshift and AWS Glue
  • Data Processing: Apache Spark and Apache Kafka
  • Data Transformation: dbt or Oracle Data Integrator (ODI)
  • Databases: Oracle or PostgreSQL
  • Programming: SQL and Python
  • Cloud Platforms: Google Cloud Platform or Microsoft Azure or Amazon Web Services (Preferred)

About Datamatics

Provides digital technology, automation, and business process management services.

Year founded
1975
Employees
10000
Industries
IT ServicesBusiness Consulting
Activities
Robotic process automationData analytics servicesBusiness process outsourcingCloud consulting servicesSoftware engineering services
Organization type
Public
Subsidiaries
Lumina DatamaticsDextara DigitalDatamatics Technologies FZ-LLCCignex
Headquarters
IN

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