Big Data and Analytics Platform Architect

About the role

ENGEEEM is looking for a Big Data and Analytics Platform Architect (M/W) for its R&D team. This is a hands-on role covering the design of data and analytics platforms using tools such as Apache Hadoop, Spark, Elasticsearch and real-time platforms like Apache Kafka, and assisting R&D data science engineers in managing and integrating AI models and products. The role runs from software architecture design through programming to deployment in the customer environment, with technical advice to customers and support for internal and external communities.

Key responsibilities

• Work with R&D Solutions Architects, Business Development teams and customers on large telecom use cases and the adoption of ENGEEM platforms for mobile experience modeling.
• Help customers with project management and implementation, from technology modeling to business requirements support.
• Develop white papers, blogs, reference implementations and presentations to help customers and partners use the QoE platform.
• Build data management platforms with microservices-based architecture and implement data processing patterns and pipelines.
• Integrate databases, NoSQL stores and appliances, citing practical implementation experiences, constraints and performance challenges.
• Design streaming and event-based architectures, from unbounded and bounded streams to state maintenance and low-latency stores, messaging and decisioning.
• Construct data consumption infrastructure such as SQL on Hadoop, API/REST services, BI, search and secondary indexing.

Required profile

• Proven experience in the Big Data / Apache Hadoop ecosystem (Hadoop Streaming, Spark, Pig, Hive) or the real-time ecosystem (Amazon Kinesis, Apache Kafka, Flink, Storm).
• Database and analytics experience (data warehousing, MPP, relational, OLTP, OLAP, NoSQL) across schema design, query tuning, data migration and integration.
• Preferred: technical degree in computer science, math or engineering (e.g. Master's); experience leading large-scale global data warehousing and analytics projects.
• Preferred: scripting skills in Python, Java, Scala or Go; experience with data lake platforms and analytics platforms in enterprises and start-ups.
• French and English speaking for customer interaction and collaboration with worldwide teams.

Required skills

• Apache Spark and data analytics pipeline development
• Apache Kafka, Elasticsearch, Hadoop, NoSQL databases
• OLTP, OLAP, MPP, in-memory and columnar data stores
• SQL, REST APIs, BI tools