Data Engineer - Full Stack Data Platform Support Engineer

Akaasa Technologies
Bethesda, MD, United States
5 days ago

Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
4 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon Web Services Big Data Cloud Computing Security Continuous Integration Information Engineering Data Infrastructure Extract Transform Load (ETL) Software Debugging Distributed Computing Environment Apache Hadoop Python (Programming Language)
+23 more
NoSQL Performance Tuning Data Streaming Enterprise Data Management Spring Cloud System Availability Apache Spark Cloudformation Containerization Data Lakes Kubernetes Infrastructure Automation Frameworks Information Technology Apache Kafka Apache Nifi Data Management Virtual Agents Restful APIs Terraform Stream Processing Data Pipelines Amazon Elastic Mapreduce (EMR) Microservices

Job description

  • Spark
  • Hadoop
  • Scala / Python
  • Amazon EMR
  • Distributed Data Processing
  • Large-Scale Batch & Streaming Workloads, We are seeking an experienced Data Engineer to support and maintain business-critical data platforms and cloud-native applications running on AWS. The ideal candidate will have strong experience with Big Data technologies, Spark, Hadoop, AWS, and distributed data processing systems. This role will focus on production support, platform reliability, troubleshooting, performance optimization, and automation of enterprise data platforms. The engineer will collaborate with SRE, Infrastructure, Development, and Business teams to ensure high availability and stability of batch and real-time data processing environments., Distinguished AI Engineer - Agentic AI Platform (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital…

  • 17 hours ago +

Requirements

  • 6+ years of overall IT experience.
  • 4+ years of experience in Data Engineering and Big Data technologies.
  • Strong hands-on experience developing Spark applications using Scala/Python.
  • Experience with distributed data processing and large-scale batch workloads.
  • Experience building cloud-native applications on AWS and Kubernetes/EKS.
  • Hands-on experience with Kafka-based streaming architectures.
  • Experience designing ETL/data ingestion pipelines using Apache NiFi.
  • Strong understanding of Hadoop ecosystem and data lake architecture.
  • Experience working with relational and NoSQL databases.
  • Experience with production support, troubleshooting, and performance optimization.
  • Knowledge of CI/CD, Infrastructure as Code, and cloud security practices.

Other Qualifications

  • Experience with microservices architecture and REST APIs.
  • Experience with Kubernetes deployments and containerized applications.
  • Knowledge of EMR cluster administration and Spark performance tuning.
  • Experience with Terraform or CloudFormation.
  • AWS Certification (Associate or Professional) preferred.
  • Strong analytical, debugging, and communication skills.

Apply for this position

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