Overview
On Site
Full Time
Part Time
Accepts corp to corp applications
Contract - W2
Contract - Independent
Skills
Extract
Transform
Load
Data Architecture
Management
Data Warehouse
Data Processing
Data Quality
Security Controls
Identity Management
Python
SQL
Java
Scala
Database
Database Administration
NoSQL
Data Modeling
Big Data
Apache Spark
Apache Hadoop
Cloud Computing
Amazon Web Services
Google Cloud
Google Cloud Platform
Microsoft Azure
Version Control
Git
Analytical Skill
Conflict Resolution
Problem Solving
Communication
Collaboration
Job Details
Python, Data Engineer, AWS
Key responsibilities
- Develop and maintain data pipelines Build, test, and maintain ETL (Extract, Transform, Load) processes to move and transform data.
- Design and manage data architecture Construct and manage data infrastructure, including data warehouses, data lakes, and databases.
- Automate data processes Use Python to automate tasks and build data processing applications.
- Integrate data sources Connect internal and external data sources and APIs, and ensure system compatibility.
- Ensure data quality and security Implement data quality checks, security controls, and access management policies.
- Collaborate with stakeholders Work with data scientists, analysts, and other teams to understand requirements and deliver solutions.
- Optimize systems Monitor system performance, troubleshoot issues, and implement optimizations for reliability and efficiency.
Required skills and qualifications
- Programming Proficiency in Python is a must. SQL and other languages like Java or Scala are also valuable.
- Databases Strong knowledge of database management systems (relational and NoSQL) and data modeling.
- Big Data Technologies Experience with big data frameworks such as Apache Spark and Hadoop.
- Cloud Platforms Familiarity with cloud services is often required, such as AWS, Google Cloud Platform, or Azure.
- Version Control Experience with version control systems like Git.
- Problem-Solving Strong analytical and problem-solving skills.
- Communication Excellent communication skills to collaborate with technical and non-technical teams.
- Education A bachelors degree in Computer Science, Engineering, or a related field is typically required.
Key responsibilities
- Develop and maintain data pipelines Build, test, and maintain ETL (Extract, Transform, Load) processes to move and transform data.
- Design and manage data architecture Construct and manage data infrastructure, including data warehouses, data lakes, and databases.
- Automate data processes Use Python to automate tasks and build data processing applications.
- Integrate data sources Connect internal and external data sources and APIs, and ensure system compatibility.
- Ensure data quality and security Implement data quality checks, security controls, and access management policies.
- Collaborate with stakeholders Work with data scientists, analysts, and other teams to understand requirements and deliver solutions.
- Optimize systems Monitor system performance, troubleshoot issues, and implement optimizations for reliability and efficiency.
Required skills and qualifications
- Programming Proficiency in Python is a must. SQL and other languages like Java or Scala are also valuable.
- Databases Strong knowledge of database management systems (relational and NoSQL) and data modeling.
- Big Data Technologies Experience with big data frameworks such as Apache Spark and Hadoop.
- Cloud Platforms Familiarity with cloud services is often required, such as AWS, Google Cloud Platform, or Azure.
- Version Control Experience with version control systems like Git.
- Problem-Solving Strong analytical and problem-solving skills.
- Communication Excellent communication skills to collaborate with technical and non-technical teams.
- Education A bachelors degree in Computer Science, Engineering, or a related field is typically required.
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