DP World
Website:
dpworld.com
Company:
https://www.linkedin.com/company/dp-world
Seniority: Not Applicable
Industries: Transportation, Logistics, Supply Chain and Storage
Job details:
Job Description
KEY ACCOUNTABILITIES
- Technical Leadership & Architecture:
- Define target architectures, engineering patterns and standards for batch/streaming integration, lakehouse design, data modelling, sharing and serving.
- Lead design reviews and technical decisions for complex or high-impact initiatives, ensuring scalability, security, resilience and reuse.
- Data Engineering & Platform Delivery:
- Design and build production-grade pipelines and reusable frameworks using SQL, Python, Spark and cloud data platform technologies.
- Establish reusable ingestion/transformation components, CI/CD and infrastructure-as-code to accelerate onboarding and reduce delivery risk.
- Reliability, Performance & Cost:
- Set standards for observability, SLAs, performance tuning, disaster recovery, incident prevention and root-cause resolution.
- Optimize compute, storage and workload design to improve platform performance, reliability and unit cost.
- Data Quality, Governance & Security:
- Embed automated data quality, lineage, metadata, access control, privacy and retention requirements into the engineering lifecycle.
- Partner with Governance and Security teams to ensure critical data products are trusted, auditable and compliant.
- Engineering Excellence & Automation:
- Drive automated testing, code quality, version control, deployment automation, coding standards and technical debt reduction.
- Evaluate emerging technologies, lead proofs of concept and convert proven capabilities into scalable enterprise standards.
- Collaboration & Mentoring:
- Mentor engineers, raise technical capability and provide hands-on support for complex troubleshooting and engineering decisions.
- Collaborate with product, analytics, AI/ML, platform and source-system teams to deliver reusable, trusted data capabilities.
Qualifications
QUALIFICATIONS, EXPERIENCE AND SKILLS
- Bachelor's degree in Computer Science , Engineering, Information Technology or a related discipline; a Master's degree is desirable.
- Minimum of 7+ years of experience in data architecture, data engineering, or a similar role, with a strong focus on designing large-scale data platforms.
- Advanced hands-on expertise in SQL, Python, Spark, distributed data processing and data modelling.
- Strong experience with cloud data platforms (Azure, AWS or GCP); Databricks/ lakehouse experience is preferred.
- Deep knowledge of batch and streaming ingestion, CDC, orchestration, APIs, data lakes/warehouses and modern data architecture patterns.
- Strong experience with Git, CI/CD, infrastructure-as-code, automated testing, observability and production engineering practices.
- Working knowledge of data governance, security, privacy, lineage, metadata management and data quality controls.
- Demonstrated ability to lead architecture/design reviews, resolve complex technical issues, mentor engineers and influence senior stakeholders.
Key Skills
- Strong leadership, collaboration, and communication skills.
- Expertise in cloud platforms and services (Azure preferred).
- Proficiency in data pipeline orchestration tools (e.g., Apache Airflow, Azure Data Factory).
- Knowledge of containerization and microservices architecture.
- Familiarity with data visualization and BI tools (e.g., Power BI, Tableau).
- Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation).
- Ability to think strategically while balancing business needs and technical solutions.
- Experience with Agile methodologies and working in a fast-paced, collaborative environment.
Desirable Qualifications
- Certifications such as Microsoft Certified: Azure Solutions Architect Expert or Google Cloud Professional Data Engineer.
- Experience with machine learning and AI workloads on data platforms.
- Knowledge of DevOps practices and CI/CD for data pipelines.
Click on Apply to know more.