Cloud Data Engineer

POSITION SUMMARY:

The Cloud Data Engineer / PostgreSQL & NoSQL Specialist is a hands-on, cloud-focused technical role that sits at the intersection of cloud database administration and data engineering. This position plays a critical role in managing, optimizing, and scaling PostgreSQL and NoSQL (DynamoDB) solutions on AWS, while also developing cloud-native ETL pipelines and data integration workflows. The ideal candidate has substantial experience in administering Amazon RDS for PostgreSQL, hands-on PostgreSQL tuning and design, as well as building automated, scalable data pipelines using tools such as Azure Data Factory. This role is foundational in supporting both real-time and batch data workloads across relational and non-relational ecosystems in a modern cloud environment.

QUALIFICATIONS:

• 5+ years of experience in data engineering and integration pipeline design, especially in cloud environments.
• 5+ years of experience working with relational databases, including deep expertise in PostgreSQL.
• 3+ years of RDS PostgreSQL administration experience, with emphasis on performance tuning, monitoring, and security.
• 3+ years of hands-on experience with AWS services, particularly RDS, S3, Lambda, Kinesis, CloudWatch, IAM, and DynamoDB.
• 3+ years of experience building ETL/ELT solutions using Azure Data Factory, with pipelines involving both cloud and on-prem sources.
• Strong skills in SQL, including writing optimized, scalable queries.
• Working knowledge of Python or Java for automation and pipeline development.
• Familiarity with NoSQL systems (e.g., DynamoDB, MarkLogic); DynamoDB preferred.
• Experience with monitoring, logging, and troubleshooting data jobs in production.
• Exposure to DevOps, CI/CD tools, and source control platforms like Git/GitHub.
• Understanding of data security best practices, including encryption, IAM, and audit logging.
• Understanding of database architecture and performance implications required.
• Experience with integrating Business Intelligence applications like PowerBI, Qlik Sense, or Tableau.
• Experience with Machine Learning and Artificial Intelligence is preferred.
• A good understanding of Data Virtualization technologies, such as Denodo, is preferred.
• Exposure to Snowflake, DBT, or other modern warehousing and transformation tools.
• Ability to multi-task effectively, work collaboratively as part of an Agile Team, and guide junior engineers.
• Excellent written and verbal communication skills, sense of ownership, urgency, and drive.

MINIMUM QUALIFICATIONS:

• Bachelor s degree in computer science, Information Systems, Engineering, Statistics, or a related field (foreign equivalent accepted).
• 3+ years of hands-on experience with AWS services for data and analytics (e.g., RDS, S3, Lambda, PostgreSQL, DynamoDB).
• 3+ years of hands-on experience with Azure Data Factory.
• 3+ years of experience with data ingestion, extraction, and integration pipelines.
• 3+ years of experience with Python or Java for data engineering and automation tasks.
• 3+ years of experience writing efficient SQL queries, including performance tuning.