Overview
Hybrid
$100,000 - $120,000
Full Time
Skills
Data Engineering
Data Processing
Data Science
Python
Business Intelligence
Dashboard
Data Analysis
Data Architecture
Data Warehouse
Machine Learning (ML)
Management
Microsoft Power BI
MongoDB
Reporting
Scalability
Semantics
Statistical Models
Thought Leadership
Analytics
Job Details
Role - Senior Data Engineer
Location - Atlanta GA
Mode of Work - Hybrid
Experience Level: 10+ years
The Need : A highly skilled and experienced Senior Data Engineer to lead and manage SQM project s data landscape. Someone with a strong background in Data Architecture, Data Science, BI reporting, hands-on expertise in data bricks, python, and mongo. The individual will be responsible for developing and implementing an overarching data strategy, driving best practices, and ensuring the scalability and efficiency of our data systems.
Required Skills and Expertise:
- Experience: 10+ years of experience in data engineering, data architecture, data science and reporting.
- Data Architecture: Proven expertise in designing and managing scalable data architectures, including data lakes, warehouses, and pipelines.
- Data Science: Strong understanding of machine learning, statistical modeling, and data analytics.
- Power BI: Understanding the dashboard, reports and underline semantic layer and queries
- Mongo: Understanding and usage of mongo for troubleshooting, development perspective
- Kubernetes/Dockers: Current env is in containers based so it is nice to have
- Python Expertise: Hands-on and advanced proficiency in Python for data engineering, automation, and analytics tasks.
Key Responsibilities:
- Design, implement, and optimize scalable data architectures to support business intelligence, analytics, reporting and machine learning initiatives.
- Develop and execute an overarching data strategy that aligns with organizational goals and objectives.
- Lead the development and management of the entire data landscape, including data pipelines, data lakes, and data warehouses.
- Leverage Python programming for data engineering tasks, including automation, data processing, and analytics.
- Provide thought leadership and guidance on emerging trends and technologies in data engineering, data science, data architecture and reporting
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