The company is seeking an experienced Senior Data Platform Engineer to lead the design, development, and maintenance of our enterprise data platforms. In this role, you will ensure that our data infrastructure is scalable, reliable, and optimized to support advanced analytics and business intelligence efforts. You will work closely with data engineers, data scientists, and IT teams to develop robust data platforms that facilitate seamless data ingestion, processing, storage, and accessibility. This is an opportunity to make significant contributions to the company's data strategy and technological advancement.
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Key Responsibilities:
- Design, build, and maintain scalable data platforms to support diverse data workloads.
- Develop and optimize ETL/ELT pipelines to ensure efficient data movement and transformation.
- Collaborate with cross-functional teams to translate business requirements into technical solutions.
- Ensure data platform security, governance, and compliance with relevant regulations.
- Monitor platform performance, troubleshoot issues, and implement improvements.
- Provide technical leadership and mentorship to junior data engineers.
- Stay updated with the latest trends and technologies in data platform engineering.
Requirements:
- Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
- 8+ years of experience in data engineering, with a focus on data platform architecture and development.
- Strong proficiency in SQL and experience with relational and NoSQL databases.
- Hands-on experience with cloud data platforms such as AWS, Azure, or Google Cloud.
- Experience with big data technologies like Hadoop, Spark, and data warehousing solutions.
- Knowledge of data governance, security, and compliance standards.
- Excellent problem-solving and communication skills.
- Proven ability to lead technical projects and mentor team members.
Required Skills & Technologies:
- SAP data extraction: OData services, RFC/BAPI, SAP Data Services, or CDS views.
- Python for async data pipelines and scheduled tasks.
- PostgreSQL for schema design and query optimization.
- Azure Data Lake Storage and Synapse Analytics.
- Microsoft Graph API for SharePoint and M365 data.
- Experience with Apache Airflow or Azure Data Factory.
- Familiarity with dbt or equivalent for transformation and quality testing.
- Knowledge of Redis for queue management and caching.
- Monitoring tools such as Azure Monitor or Prometheus/Grafana.
- Experience with Docker for containerized pipeline jobs.
- Familiarity with Infrastructure-as-code such as Terraform.
Benefits:
- Paid Time Off
- Performance Bonus
- Training & Development
Location: Dubai, Dubai, United Arab Emirates
Work Conditions: On-site, Full-time
