Perfict Global, Inc.
Data Engineer
Perfict Global, Inc. - Jersey City, New Jersey, United States, 07390
Work at Perfict Global, Inc.
Overview
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Overview
Data Engineer -- C2C -- Jersey City NJ, Columbus, OH (Only locals)
Visa - USC, H1B, H4EAD
Required Skills & Experience
Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field. 9+ years of experience in Data Engineering or related roles. Strong experience with SQL and data manipulation. Proficiency in programming languages such as
Python ,
Scala , or
Java . Hands-on experience with
ETL tools
(e.g., Apache Airflow, Talend, Informatica). Experience with
cloud platforms
such as
AWS ,
Azure , or
Google Cloud Platform . Familiarity with data warehousing tools like
Snowflake ,
Redshift ,
BigQuery , or
Azure Synapse . Understanding of
data modeling ,
data governance , and
data quality frameworks . Experience with
big data tools
(e.g., Spark, Hadoop) and
streaming platforms
(e.g., Kafka, Kinesis) is a plus. Preferred Qualifications
Experience with containerized environments (e.g., Docker, Kubernetes). Exposure to DevOps and CI/CD pipelines (Git, Jenkins, Terraform). Knowledge of machine learning pipelines and MLOps. Relevant cloud certifications (e.g., AWS Certified Data Analytics - Specialty).
Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field. 9+ years of experience in Data Engineering or related roles. Strong experience with SQL and data manipulation. Proficiency in programming languages such as
Python ,
Scala , or
Java . Hands-on experience with
ETL tools
(e.g., Apache Airflow, Talend, Informatica). Experience with
cloud platforms
such as
AWS ,
Azure , or
Google Cloud Platform . Familiarity with data warehousing tools like
Snowflake ,
Redshift ,
BigQuery , or
Azure Synapse . Understanding of
data modeling ,
data governance , and
data quality frameworks . Experience with
big data tools
(e.g., Spark, Hadoop) and
streaming platforms
(e.g., Kafka, Kinesis) is a plus. Preferred Qualifications
Experience with containerized environments (e.g., Docker, Kubernetes). Exposure to DevOps and CI/CD pipelines (Git, Jenkins, Terraform). Knowledge of machine learning pipelines and MLOps. Relevant cloud certifications (e.g., AWS Certified Data Analytics - Specialty).