Data Engineer
CYNET SYSTEMS INC.
Mason, United States of America
26 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
Senior Compensation
$ 125KJob location
Mason, United States of America
Tech stack
Airflow
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Big Data
Continuous Integration
Information Engineering
Data Governance
Data Integration
ETL
Data Sharing
Data Visualization
Data Warehousing
DevOps
Dimensional Modeling
Revision Control Systems
Hadoop
Python
Power BI
SQL Stored Procedures
SQL Databases
Systems Integration
Tableau
Unstructured Data
Data Ingestion
Snowflake
Spark
PySpark
Amazon Web Services (AWS)
Real Time Data
Data Pipelines
Databricks
Job description
- Design, develop, and maintain scalable data pipelines and workflows using Snowflake and AWS services.
- Implement data ingestion, transformation, and integration processes for structured and unstructured data.
- Develop optimized Snowflake objects (tables, views, streams, tasks, stored procedures).
- Build and manage ELT pipelines using tools such as AWS Glue, Airflow, or other orchestration frameworks.
- Collaborate with data analysts, architects, and business stakeholders to gather data requirements and deliver high-quality solutions.
- Perform data modeling (dimensional & warehouse modeling) to support reporting and analytics use cases.
- Optimize data processes for performance, scalability, and cost-efficiency in Snowflake.
- Implement data governance, security, and compliance best practices.
- Monitor, troubleshoot, and resolve issues related to data pipelines and integrations.
- Ensure data quality, integrity, and availability across systems.
Requirements
- 7+ years of experience in Data Engineering or related roles.
- Strong hands-on experience with Snowflake (SnowSQL, Snowpipe, Streams, Tasks, Data Sharing).
- Experience in AWS ecosystem (S3, Redshift, Glue, Lambda, EMR).
- Proficiency in SQL and one programming language (Python / PySpark preferred).
- Experience in ETL/ELT tools and data integration frameworks.
- Strong knowledge of data warehousing concepts and dimensional modeling.
- Experience with big data technologies (Spark, Hadoop, Databricks - optional but preferred).
- Familiarity with CI/CD, DevOps practices, and version control tools., * Experience with real-time data ingestion and streaming pipelines.
- Exposure to data orchestration tools (Airflow, Step Functions, etc.).
- Knowledge of data visualization tools (Power BI, Tableau).
- Experience in US healthcare domain (preferred for Elevance-type engagements).