Data Engineer (AWS) at NTT DATA

Guadalajara, jalisco, Mexico -

Full Time

Start Date

Immediate

Expiry Date

18 Mar, 26

Salary

0.0

Posted On

18 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, AWS, Python, Java, Scala, PySpark, Data Lake House Solutions, Snowflake, Databricks, Cloud Storage, HDFS, S3, Data Integration, Spark, Kafka, Agile

Industry

IT Services and IT Consulting

Description

Design and implement tailored data solutions to meet customer needs and use cases, spanning from streaming to data lakes, analytics, and beyond within a dynamically evolving technical stack. Provide thought leadership by recommending the most appropriate technologies and solutions for a given use case, covering the entire spectrum from the application layer to infrastructure. Demonstrate proficiency in coding skills, utilizing languages such as Python, Java, and Scala to efficiently move solutions into production while prioritizing performance, security, scalability, and robust data integrations. Collaborate seamlessly across diverse technical stacks, including Cloudera, Databricks, Snowflake, and AWS. Develop and deliver detailed presentations to effectively communicate complex technical concepts. Generate comprehensive solution documentation, including sequence diagrams, class hierarchies, logical system views, etc. Adhere to Agile practices throughout the solution development process. Design, build, and deploy databases and data stores to support organizational requirements. 4+ years of experience supporting Software Engineering, Data Engineering, or Data Analytics projects specifically with AWS. 4+ years of experience on at least one of the following: PySpark or Scala or Data lake house solutions on AWS 2+ years of experience leading a team supporting data related projects to develop end-to-end technical solutions. Demonstrate production experience in other core data platforms such as Snowflake, Databricks, Azure, GCP, Hadoop, and more. Possess hands-on knowledge of Cloud and Distributed Data Storage, including expertise in HDFS, S3, ADLS, GCS, Kudu, ElasticSearch/Solr, Cassandra, or other NoSQL storage systems. Exhibit a strong understanding of Data integration technologies, encompassing Spark, Kafka, eventing/streaming, Streamsets, NiFi, AWS Data Migration Services, Azure DataFactory, Google DataProc. Showcase professional written and verbal communication skills to effectively convey complex technical concepts.

Responsibilities

Design and implement data solutions tailored to customer needs, covering various technologies from streaming to data lakes. Collaborate across technical stacks and deliver presentations while adhering to Agile practices.