Data Analytics Platform Engineer

The Data Analytics Platform Engineer will be instrumental in implementing architecture and engineering processes, and best practices to enable application hosting in environments on-premises, on public cloud platforms, or as hybrid deployments. The candidate should have knowledge of data analytics solutions, modern micro-services architectures, Kubernetes, and cloud infrastructure. The role is responsible for owning the exploration, technical advisory, and development for platforms and products ensuring success in scaling data analytics services using secure, safe, and robust architecture(s).

Responsibilities: 

• Design and deliver data analytics Platform as a Service solution(s) as turn-key offerings to support Citi lines of businesses.
• Contribute and execute the strategy, architecture, and feature roadmap for supporting and evolving Citi’s Big Data Enterprise Analytics Platform (EAP) Services and related data analytics solutions.
• Drive platform modernization efforts to support storage and compute decoupling and enablement of elastic compute capabilities.
• Work on designing hybrid cloud architecture, evaluations, and enablement efforts to build solutions using IaaS, PaaS, and SaaS capabilities.

Qualifications: 

• Strong understanding of private and public cloud technologies, architectures, network designs, etc., along with working experience of one of the major public cloud service providers – AWS, GCP, or Azure. GCP experience preferred.
• Understanding of platform architecture, high availability, fail-over, disaster recovery planning, and implementation considerations based on service level agreements. 
• Experience in engineering platform solutions using various hosting options including physical machines, virtual machines, containers, and Kubernetes.
• Hands-on experience with Big Data technologies like Hadoop, Spark, Hive, Impala, HBase, YARN, etc. using distribution from Cloudera or MapR. Cloudera experience preferred.
• Experience with developing and managing Data Lakes and Analytics platforms using technologies like Hadoop/HDFS, Object Storage (S3, GCS, or similar), Apache Spark, Apache Trino, etc.
• Knowledge of business intelligence & reporting solution such as Tableau, Qlik, etc. and familiarity with large scale analytical platforms / products such as Python, H2O, Dataiku, Google Vertex AI, etc.
• Hands on work with one of the major programming languages Java, Python, Ruby, etc. 
• Working knowledge of Infrastructure as Code (IaC) and CI/CD processes and tools.
• Understanding of data life cycle – data acquisition, data quality management, data governance, and metadata management.
• Excellent written and verbal communication skills. 
• Capable of building, articulating, and presenting new ideas to technical, non-technical, and business communities.  
• Experience managing vendor interactions for troubleshooting sessions, enhancement requests, and guiding vendor roadmaps to meet Citi standards and functional requirements.  
• Self-starter able to work with minimal supervision and in a global team of members with diverse skills and backgrounds.

Preferred Qualifications:

• Experience in moving application workloads from on-premises Hadoop platforms to GCP (Google Cloud Platform) IaaS services like Google Cloud Engine, and Google Cloud Storage and/or PaaS services like Dataproc, Big Query, and Big Table. 

Education Level: Bachelor's degree required; master’s degree preferred 

Experience: 8 or more years of experience in relevant technologies

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Qualified applicants will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

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