Data Engineer وقت كامل وظيفةمنذ سنة - تكنولوجيا المعلومات والاتصالات - Beirut - 899 الآراء
Do you have a passion for data, analytics, insights andtechnology? AI Venture Labsis looking for a talented Data Engineer who wants to get their hands onlarge and complex datasets and databases, with deep knowledge of SQL database design,distributed systems and computer science, who’s interested in working alongsidedata scientists to build and deploy cutting-edge analytical capabilities anddrive business impact.
· Develop andmaintain data pipelines including solutions for data collection, management andusage.
· Work closelywith Data Scientists to optimize and reengineer model code to be modular,efficient and scalable, and to deploy models to production.
· Maintain andenhance data and computation platforms.
· Develop andimplement solutions for data quality validation and continuous improvement.
· Manage,execute and monitor weekly and monthly production operations; resolve andescalate production issues as appropriate.
· Partner withdata scientists, PMs, engineers and business stakeholders to understandbusiness and technical requirements, plan and execute projects, and communicatestatus, risks and issues.
· Perform rootcause analysis of system and data issues and develop solutions as required.
· BS incomputer science or Information Systems.
· Proficient inSQL and database architectures.
· Experienceworking with cloud-based technologies, including relational databases, datawarehouse, big data (e.g., Hadoop, Spark), orchestration/data pipeline tools.
· Experiencewith Azure Analytics stack, e.g., Azure Data Lake, Azure Databricks, Azure DataFactory.
· Experiencewith ETL data pipelining concept.
· Proficient inPower BI.
· Experienceworking in software engineering, and can demonstrate best practices for projectmanagement, quality control, and product development.
· Proven trackrecord of collaborative development in an agile team environment.
· Experiencewith R, Python and libraries for data exploration, modeling and visualization.
· Machine learningexperience
· Experiencewith infrastructure automation technologies like Docker and Kubernetes.
· Experiencebuilding APIs and services using REST.