Data Engineer (Ref# DE429RV)

KYYBA, Inc
Farmington Hills, United States of America
1 month ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Junior

Job location

Farmington Hills, United States of America

Tech stack

Amazon Web Services (AWS)
Azure
Cloud Computing
Computer Engineering
Data Architecture
Information Engineering
Data Governance
Data Integration
Data Integrity
ETL
Data Systems
Document-Oriented Databases
Github
Python
SQL Databases
Unstructured Data
Data Storage Management
Google Cloud Platform
System Availability
Data Lake
Kubernetes
Information Technology
GraphQL
Terraform
Data Pipelines
Docker
Databricks

Job description

Job Duties: Develop, maintain, test, and evaluate data engineering solutions to support advanced analytics and business intelligence initiatives. Implement data architecture and design solutions as defined by the Advanced Analytics Data Architect, ensuring scalability, performance, and data integrity. Execute complex data engineering projects focused on collecting, parsing, managing, analyzing, and visualizing large and diverse datasets from multiple sources and platforms. Design and develop data pipelines, ETL (Extract, Transform, Load) processes, and data integration workflows to enable efficient movement and transformation of structured and unstructured data. Collaborate with data scientists, analysts, and business stakeholders to transform raw data into actionable insights that support data-driven decision-making. Optimize data storage and retrieval systems for performance and reliability across on-premises and cloud-based environments. Conduct testing, validation, and quality assurance of data systems to ensure accuracy, completeness, and compliance with data governance standards. Monitor, troubleshoot, and enhance existing data solutions to improve efficiency and maintain high system availability. Document data workflows, technical specifications, and operational procedures for ongoing support and knowledge sharing. Use of Amazon Web Services (AWS), Azure, Google Cloud Platform (GCP), Azure Databricks, Delta Lake, GraphQL, GitHub, Python, SQL, Docker, Kubernetes, and Terraform.

Requirements

Position requires 1 year of experience with ETL, Amazon Web Services (AWS), Google Cloud Platform (GCP), Python, and SQL., Requirements: Master's degree or foreign academic equivalent in Data Science, Data/Business Analytics, Computer Science, Computer Engineering, or a related field. Plus 2 years of experience in the job offered or a related occupation including Data Scientist or related experience. Position requires 1 year of experience with ETL, Amazon Web Services (AWS), Google Cloud Platform (GCP), Python, and SQL. 40hrs/week.

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