Data Engineer

CYNET SYSTEMS INC.

Mason, OH, United States

2 months ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

7 years minimum

Compensation

$114,400.0 - $124,800.0

Working hours

Regular working hours

Job source

careerjet.com

Tech stack

Airflow Amazon Web Services Amazon S3 Big Data Continuous Integration Information Engineering Data Governance Data Integration Extract Transform Load (ETL) Data Sharing Data Visualization Data Warehousing

+19 more

DevOps Dimensional Modeling Revision Control Systems Apache Hadoop Python (Programming Language) Power BI SQL Stored Procedures SQL Databases Systems Integration Tableau (Software) Unstructured Data Data Ingestion Snowflake Apache Spark Pyspark AWS Glue 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).