Title: Cloud Engineering- Data focus
Location: Rochester, NY; hybrid candidates with 10% travel required
The objective of the Role: Cloud Engineer will be a key technical resource responsible for implementing AWS data services, creating ETL/ELT pipelines, and supporting data solutions that help our customers unlock insights from their data. You will work closely with Cloud Architects and senior team members to deliver high-quality solutions that meet customer requirements.
Top candidates will have the following:
1. Technical familiarity with AWS data services and modern data engineering practices
2. Hands-on experience with ETL/ELT processes and data transformation
3. Ability to write and optimize SQL queries across various database platforms
4. Knowledge of data modeling concepts and best practices
5. Strong analytical and problem-solving skills
6. Eagerness to learn new technologies and keep up with cloud innovations
7. Excellent communication skills with the ability to explain technical concepts clearly
8. Attention to detail and commitment to solution quality
9. Collaborative mindset with strong teamwork capabilities
10. Experience or interest in automation and infrastructure as code
Required Experience for the Role:
1. Must have 1-3 years of experience with cloud technologies, preferably AWS
2. Must have AWS Certified Cloud Practitioner certification or ability to obtain within 3 months
3. Must have experience with SQL and at least one programming language (Python, Java, etc.)
4. Must have basic understanding of data engineering concepts and data lifecycle management
5. Must have familiarity with AWS data services such as S3, RDS, Glue, and Redshift
6. Must have understanding of data security and access control principles
7. Must have experience with version control systems (Git)
8. Must have knowledge of infrastructure as code concepts
Preferred Experience for the Role:
1. AWS Solutions Architect Associate or AWS Data Analytics Specialty certification
2. Experience with AWS Lambda, Step Functions, or other serverless technologies
3. Familiarity with data visualization tools such as QuickSight or Tableau
4. Knowledge of big data technologies such as Hadoop, Spark, or Hive
Responsibilities, including success measures and KPIs:
1. Implementing data pipelines using AWS services such as Glue, Lambda, Step Functions, and EMR
2. Creating and maintaining data extraction, transformation, and loading processes
3. Configuring and optimizing AWS database services including RDS, Aurora, Redshift, and DynamoDB
4. Implementing data lakes using S3 and related AWS services
5. Writing and testing SQL queries and stored procedures
6. Documenting technical solutions and providing knowledge transfer to customers
7. Supporting the implementation of data governance and security controls
8. Troubleshooting and resolving issues with data pipelines and services
9. Participating in code reviews and implementing feedback
10. Assisting with proof-of-concept implementations for customer engagements
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