Lead AWS Data/Generative AI Data Enginee
AcquityNode LLC
United States
7 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
$121,347.0 - $146,120.0
Working hours
Regular working hours
Job source
Tech stack
Java (Programming Language)
Agile Methodology
Artificial Intelligence
Amazon Web Services
Amazon Elastic Compute Cloud
Amazon S3
Data Analysis
Bash Shell
Big Data
Cloud Database
Code Review
Information Engineering
+33 more
Extract Transform Load (ETL)
Dataspaces
Data Systems
Data Warehousing
Database Design
Dimensional Modeling
Apache Hadoop
Apache Hive
Python (Programming Language)
Linked Data
Machine Learning
Microsoft SQL Server
Oracle (Applications)
Scrum Methodology
Cloud Services
Azure Data Lake
Shell Script
Software Engineering
SQL Databases
Talend
Cloud Platform System
Data Ingestion
Apache Spark
Generative AI
Data Strategy
Vba Programming Language
Integration Frameworks
AWS Data Analytics
Data Management
Functional Programming
Restful APIs
Looker Analytics
Data Pipelines
Job description
- Lead the design, development, and optimization of large-scale data architectures utilizing AWS cloud services such as Azure Data Lake, Hadoop, Spark, and related big data systems.
- Architect and implement robust ETL pipelines using tools like Talend, Informatica, and custom scripting (Python, Bash) to facilitate seamless data ingestion, transformation, and loading into data warehouses.
- Collaborate with cross-functional teams to develop innovative generative AI models through model training, fine-tuning, and deployment within cloud environments.
- Manage and enhance data models including dimensional modeling and linked data structures to support business intelligence applications.
- Oversee the integration of diverse data sources such as SQL databases (Oracle, Microsoft SQL Server), cloud databases, and RESTful APIs to ensure comprehensive data coverage.
- Drive continuous improvement in query management, database design, and analytics processes using tools like Looker and other BI platforms.
- Promote agile development practices by participating in sprint planning, code reviews, and documentation to ensure high-quality deliverables aligned with project goals., Join us as a Lead AWS Data/Generative AI Data Engineer to shape the future of our data ecosystem! Your expertise will drive innovation across our cloud-based big data systems while empowering teams with actionable insights through advanced analytics and AI models. We are committed to fostering an inclusive environment where your skills will make a meaningful impact!
Requirements
- Extensive experience with AWS cloud services including S3, EC2, Lambda, and related infrastructure for scalable data solutions.
- Proficiency in programming languages such as Java and Python for software development and automation tasks.
- Strong knowledge of big data technologies including Hadoop ecosystem components (Hive, Spark), Azure Data Lake, and Apache Hive.
- Expertise in data management integration techniques involving ETL processes with tools like Talend or Informatica; solid understanding of SQL databases including Oracle and SQL Server.
- Demonstrated ability to design effective data models using dimensional modeling principles for warehousing purposes.
- Familiarity with business intelligence tools such as Looker for reporting and analysis; experience with query management is essential.
- Skilled in developing ETL pipelines for large datasets; experience with shell scripting (Bash), VBA, RESTful APIs, and cloud database management is highly desirable.
- Strong analysis skills combined with a solid foundation in analytics methodologies; experience with model training for generative AI applications is a plus.
- Knowledge of agile methodologies to foster collaborative project execution within fast-paced environments.
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