Data Engineer
Volt Information Sciences Inc
Las Vegas, United States of America
yesterday
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
Senior Compensation
$ 150KJob location
Las Vegas, United States of America
Tech stack
API
Agile Methodologies
Artificial Intelligence
Amazon Web Services (AWS)
Data analysis
Azure
Business Intelligence
Big Data
Cloud Computing
Code Review
Information Systems
Computer Programming
Continuous Integration
Data Architecture
Data Governance
Data Infrastructure
Data Migration
Data Warehousing
Infrastructure as a Service (IaaS)
Python
Enterprise Messaging Systems
NoSQL
Data Processing
Test Driven Development
Data Ingestion
Azure
Spark
Hdinsight
Information Technology
Kafka
Video Streaming
REST
Stream Analytics
Data Pipelines
Databricks
Job description
As a Senior Data Engineer, you will be responsible for :
- Design, develop, and maintain real-time or batch data pipelines to process and analyze large volumes of data. Designs and develops programs and tools to support ingestion, curation, and provisioning of complex first party and third-party data to achieve analytics, reporting, and data science. Design and develop Advanced Data Products and Intelligent API's. Monitors the system performance by performing regular tests, troubleshoots, and integrates new features.
- Lead in analysis of data and the design the data architecture to support BI, AI/ML and data products.
- Designs and implements data platform architecture to meet organization analytical requirements. Ensures the solution designs address operational requirements such as scalability, maintainability, extensibility, flexibility, and integrity.
- Provide technical leadership and mentorship to team members. Leads peer development and code reviews with focus on test driven development and Continuous Integration and Continuous Development (CICD).
Requirements
- Bachelor's degree in computer science, information systems, data science, management information systems, mathematics, physics, engineering, statistics, economics, and/or a related field required.
- Master's degree in computer science, information systems, data science, management information systems, mathematics, physics, engineering, statistics, economics, and/or a related field preferred.
- Minimum of eight (8) years of experience as a data engineer with full-stack capabilities
- Minimum of ten (10) years of Experience in programming
- Minimum of five (5) years in Cloud technologies like Azure, Aws or Google.
- Strong SQL Knowledge
- Experience in ML and ML Pipeline a plus
- Experience in real-time integration, developing intelligent apps and data products.
- Proficiency in Python and experience with CI/CD practices
- Strong background in IAAS platforms and infrastructure
- Hands-on experience with Databricks, Spark, Fabric, or similar technologies
- Experience in Agile methodologies
- Hands-on experience in the design and development of data pipelines and data products
- Experience in developing data ingestion, data processing, and analytical pipelines for big data, NoSQL, and data warehouse solutions.
- Hands-on experience implementing data migration and data processing using Azure services: ADLS, Azure Data Factory, Event Hub, IoT Hub, Azure Stream Analytics, Azure Analysis Service, HDInsight, Databricks Azure Data Catalog, Cosmo Db, ML Studio, AI/ML, etc.
- Extensive experience in Big Data technologies such as Apache Spark and streaming technologies such as Kafka, EventHub, etc.
- Extensive experience in designing data applications in a cloud environment.
- Intermediate experience in RESTful APIs, messaging systems, and AWS or Microsoft Azure.
- Extensive experience in Data Architecture and data modeling
- Expert in data analysis and data quality frameworks.
- Knowledgeable with BI tools such as Power BI and Tableau.
- May occasionally work evenings and/or weekends.
Salary Range: $120,000 - $150,000 per year
*Salary range offered to a successful candidate will be based on several factors, including the candidate's education, work experience, work location, specific job duties, certifications, etc.