Join NTT DATA, a global leader in technology services, as a Senior POD Engineer. We are seeking innovative and passionate individuals to contribute to our dynamic team. You will play a crucial role in designing and implementing cutting-edge data solutions that address diverse customer needs, from real-time streaming to comprehensive data lakes and advanced analytics.

This role offers the opportunity to work with a forward-thinking organization committed to accelerating client success and making a positive societal impact through responsible innovation. If you thrive in an inclusive and adaptable environment, we encourage you to apply.

As a Senior POD Engineer, you will architect and deploy bespoke data solutions, including streaming, data lakes, and analytics platforms within a flexible tech stack. You'll provide expert guidance on technology selection, ensuring optimal solutions from application layers to infrastructure. Leveraging your coding prowess in Python, Java, and Scala, you will drive solutions into production, emphasizing performance, security, scalability, and robust data integration.

Your responsibilities will extend to seamless collaboration across platforms like Cloudera, Databricks, Snowflake, and AWS. You will craft detailed presentations to articulate complex technical concepts and produce comprehensive solution documentation, including sequence diagrams and system views. Adherence to Agile methodologies and the design, construction, and deployment of databases and data stores are also key aspects of this role.

We are looking for candidates with at least 4 years of experience in Software Engineering, Data Engineering, or Data Analytics projects. A minimum of 2 years of experience leading data-focused projects to develop end-to-end technical solutions is essential. The ability to travel at least 25% of the time is also required.

While not mandatory, a Bachelor's or Graduate degree is preferred. Preferred skills include production experience with core data platforms such as Snowflake, Databricks, AWS, Azure, GCP, and Hadoop, as well as hands-on knowledge of cloud and distributed data storage systems like HDFS, S3, ADLS, GCS, Kudu, Elasticsearch/Solr, and Cassandra. Expertise in data integration technologies including Spark, Kafka, and eventing/streaming tools like Streamsets and NiFi is highly valued. Strong written and verbal communication skills are also important.