Senior Data Architect

1 week ago

Abu Dhabi, Abu Dhabi, United Arab Emirates NMDC Group Full time
Roles and responsibilities
  • Design, architect, andimplement a scalable data platform for the businessunit's specific needs that supports data-drivendecision-making, operations efficiency, and democratization ofdata
  • Design a data platform architecture thatpromotes seamless integrations with 3rd party applications,Corporate IT systems including ERP, and in-house builtsolutions
  • Act as the primary liaison betweenthe business unit technology team and Corporate IT, ensuring thatdata architecture, governance standards, cyber security andcompliance protocols are maintained
  • Establishprocess to ensure federation of corporate IT policies within thebusiness unit
  • Lead and mentor a team of dataengineers to build all necessary data pipelines and infrastructuresinspired by latest best practices in modular design andmicroservices.
  • Collaborate with businessstakeholders, product managers, software engineers, and other dataengineers to ensure the data platform supports the innovationambitions of the business unit including Data Science, MachineLearning, and Artificial Intelligence
  • Developand implement logical and physical data models that meet the uniqueneeds of the business unit while aligning with Corporate ITstandards for data architecture.
  • Develop andoversee data ETL processes guaranteeing optimizedperformance
  • Maintain detailed documentation ofthe data architecture, data flows, and integrations to ensuretransparency and consistency across both business unit andcorporate data systems.

Qualifications:

  • Bachelor's degree inComputer Science, Computer Engineering, Data Science or a relatedfield
  • A Master in the field is aplus
  • 8 years experience in data architecture,data engineering, with significant experience in enterprise datadesign.
Desired candidate profile

1.Data ArchitectureDesign

  • ArchitectingData Solutions: Design and implement scalable andhigh-performance data architectures that meet both current andfuture business needs.
  • DataModeling: Develop data models (conceptual, logical,and physical) to structure and organize data in a way thatmaximizes its value while ensuring data integrity andefficiency.
  • Big DataSolutions: Design and implement data architecturesto handle large volumes of data, including the use ofNoSQL databases (e.g.,Cassandra,MongoDB) and distributedsystems (e.g., Hadoop,Spark).
  • CloudArchitecture: Create and manage cloud-based dataarchitectures using platforms likeAWS, GoogleCloud, orAzure.
  • DataWarehousing: Lead the design and implementation ofdata warehouses, data lakes, and ETL (Extract, Transform, Load)pipelines to consolidate data from multiplesources.
  • DataIntegration: Design and implement systems for dataintegration, ensuring data flows seamlessly between systems and isharmonized for analysis.

2.Data Governance andSecurity

  • DataGovernance: Establish policies and frameworks formanaging data quality, consistency, and availability across theorganization.
  • DataSecurity: Ensure that data is securely stored andprocessed, adhering to privacy regulations (e.g.,GDPR,CCPA) and implementing encryption,access control, and auditingmeasures.
  • Compliance:Ensure that data architecture complies with industry standards,security practices, and regulatoryrequirements.
  • MetadataManagement: Implement and manage metadata systems totrack and govern the usage, lineage, and transformation ofdata.

3. CollaborationandLeadership

  • Cross-DepartmentCollaboration: Work closely with teams such as dataengineering, business intelligence, data science, and productmanagement to define data needs and ensure alignment across theorganization.
  • Mentoring:Provide leadership and mentorship to junior data architects, dataengineers, and other technical teams to ensure the adoption of bestpractices.
  • StakeholderCommunication: Present and explain technicalconcepts to non-technical stakeholders, including senior managementand business leaders, helping them understand the strategic valueof data architecture.
  • ProjectManagement: Lead or participate in the planning andexecution of data-related projects, ensuring they are delivered ontime and meet business goals.

4.Optimization and PerformanceTuning

  • DataProcessing Optimization: Continuously assess andimprove the performance of data systems, including optimizingqueries, data pipelines, and storagesolutions.
  • Scalability:Ensure that data solutions are scalable to handle growing datavolumes and changing businessneeds.
  • DisasterRecovery: Design and implement disaster recoverystrategies to ensure that data is protected and can be quicklyrestored in case of a failure.

5.Innovation andStrategy

  • EvaluateNew Technologies: Stay up-to-date with the latesttrends and technologies in data architecture, including AI/ML, datalakes, real-time analytics, and cloudplatforms.
  • Long-TermStrategy: Define and implement the long-term datastrategy, ensuring that the architecture aligns with the evolvingneeds of the business and technologicaladvancements.
  • EmergingTrends: Explore and incorporate new technologies,tools, and best practices to improve data architecture, such asdata mesh, datafabric, and serverlessarchitectures.
Key Skills
Data Processing,DataCollection,Data Analysis and Reporting
Employment Type : Full-time
Department / Functional Area: DataEngineering
Experience: years
Gender: Male
Vacancy: 1

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