الوصف الوظيفي
Data Engineer plays a critical role in data and analytics life cycle and significantly contributes to production grade data and analytics solutions. The role requires one to demonstrate Big Data, Engineering and Cloud expertise.Expected to bring technical thought leadership. Besides contributing in individual capacity, this role also leads and develops Data and Analytics talent
14-16+ years of relevant experience
Bachelors degree in computer science, information technology or equivalent educational qualification
• Design, build, and maintain robust ETL/ELT pipelines on cloud(Azure) or on-prem to collect, ingest and store large volumes of structured and unstructured data for batch/real time processing
• Solve complex business problems using data and advanced technologies
• Monitor, optimize, and troubleshoot data pipelines to ensure reliability, scalability, and performance
• Ensure data processing, quality, security, and compliance guidelines, policies and standards are followed
• Collaborate with multiple partners from Business, Technology, Operations and D&A capabilities (Data Governance, Data Quality, Data Modeling, Data Architecture, Data science, DevOps, BI & insights)
• Independently lead design, solutioning & estimations
• Provide people leadership: coach, develop and engage talent
• SQL, Python/Scala
• NoSql and distributed databases (Hbase, Cosmos DB)
• ETL pipleine design and development; Solutioning and estimation
• Big Data Frameworks : Apache Spark, Hadoop, Hive
• Cloud platforms: Azure data factory, Eventhub, Azure functions, Synapse, Databricks
• Datawarehouses, data marts, data lakes
• Medallion architecture, and other design patterns
• Performance tuning, optimization, and data quality validation
• Real-time and batch data processing , streaming pieplines with Spark
• Evidence of thought leadership
•Communication skills, analytical skills, structured problem-solving skills,mentorship & people leadership skills
• Storytelling skills , Partner & Stakeholder engagement experience
• People leadership: talent development & engagement experience
• DevOps practices: Git, AzureDevops, CI/CD pipelines
• Unix shell scripting, MongoDB, Nifi
• Lambda architecture, Kappa Architecture
• Banking Financial Services and Insurance domain knowledge
لقد تمت ترجمة هذا الإعلان الوظيفي بواسطة الذكاء الاصطناعي وقد يحتوي على بعض الاختلافات أو الأخطاء البسيطة.
