Data Engineer

Leidos, Inc.
New York, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Compensation
$ 167K

Job location

New York, United States of America

Tech stack

Java
Agile Methodologies
Airflow
Amazon Web Services (AWS)
Data analysis
Automation of Tests
Azure
Google BigQuery
Cloud Computing
Cloud Database
Databases
Continuous Delivery
Continuous Integration
Information Engineering
Data Infrastructure
Data Integration
ETL
Data Migration
Data Systems
Data Warehousing
Amazon DynamoDB
Data Flow Control
Hive
Python
NoSQL
Performance Tuning
Regression Testing
Scala
Software Deployment
Data Streaming
Systems Integration
Virtual Machines
Private Cloud Environment
Data Processing
Scripting (Bash/Python/Go/Ruby)
Cloud Platform System
System Availability
Delivery Pipeline
Snowflake
Spark
AWS Lambda
Amazon Web Services (AWS)
GIT
Cloudformation
Gitlab-ci
Kubernetes
Low Latency
Amazon Web Services (AWS)
Data Analytics
Amazon Web Services (AWS)
Real Time Data
Kafka
Data Pipelines
Serverless Computing
Amazon Web Services (AWS)
Docker
Jenkins
Redshift
Databricks

Job description

  • $92,300-166,850 per year Description We are seeking a dynamic Travel Construction Manager (Civil Engineer) to support the National Airspace System Integration Support Contract (NISC IV). In this role, yo…

  • 3 days ago

Requirements

Candidate need to have colab set up ready with Gmail account so they can code on the L1 interview Must have : Languages & Scripting: Spark, Python, Java, Scala, Hive, Kafka, SQL Cloud Platforms: AWS Data Warehousing & Analytics: Redshift or Snowflake or Big Query Data Integration & ETL: AWS Glue, Aws EMR, Spark, Data Bricks CI/CD: AWS Code Pipeline, Jenkins, CloudFormation, Docker, Kubernetes JD :

  • Results-driven Data Engineer with a decade of expertise in Data engineering across cloud platforms with a total of 12 years in IT.
  • Extensive experience utilizing Google Cloud Platform (GCP) services, including BigQuery, Dataflow, Dataprep, and Pub/Sub, for data engineering solutions.
  • Proficient in building and managing GCP data pipelines with tools like Cloud Composer and Cloud Dataflow.
  • Proven ability in developing and deploying applications on Google Kubernetes Engine (GKE).
  • Strong background in implementing security and compliance on GCP, ensuring data privacy and regulatory adherence.
  • Track record of optimizing cost and resource usage within GCP environments.
  • Skilled in AWS services such as Amazon EMR, Redshift, and Glue for efficient data processing.
  • Expertise in architecting scalable, cost-effective solutions on AWS, with proficiency in configuring AWS Lambda for serverless computing.
  • Adept at setting up AWS Kinesis streams to process real-time data, enhancing system responsiveness and data-driven decision-making.
  • Proficient in leveraging AWS DynamoDB to create scalable, low-latency NoSQL databases for dynamic applications.
  • Deep expertise in optimizing and managing Amazon Redshift data warehouses to deliver high-performance analytics and business insights.
  • Experienced in integrating AWS services into CI/CD pipelines, streamlining automation for continuous integration, delivery, and deployment.
  • Skilled in setting up and securing AWS Virtual Private Cloud (VPC) environments.
  • Proficient in managing Azure virtual machines (VMs) for cloud infrastructure operations.
  • Extensive experience managing on-premises data infrastructure, including data warehouses and databases.
  • Familiar with AWS DevOps practices for continuous integration and deployment.
  • Expertise in using Git for version control in DBT projects, ensuring proper tracking and documentation of data model changes.
  • Skilled in performance optimization and tuning of on-premises data systems.
  • Proficient in data migration strategies between on-premises and cloud environments.
  • Strong troubleshooting skills in resolving issues within on-premises data systems.
  • Proven ability to maintain high availability and disaster recovery solutions in on-premises environments.
  • Experienced in implementing CI/CD pipelines using tools like Jenkins and GitLab CI/CD.
  • Adept in automated testing processes, including unit, integration, and regression testing.
  • Skilled in gathering and analyzing project requirements to ensure alignment with business goals.
  • Experienced in Agile project management, contributing to successful outcomes through data-driven analytics and collaborative teamwork

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