Data Engineer

Job Title: Data Engineer
Location: Charlotte, NC
Experience: 13 years
Employment Type: W2
Job Summary:
We are seeking an experienced Data Engineer to design, build, and optimize scalable data pipelines and ETL processes on Google Cloud Platform (GCP). The ideal candidate should have strong hands-on experience with data extraction, transformation, and loading (ETL), and proficiency in Java or Python for automation and scripting.
Key Responsibilities:
Design, develop, and maintain ETL pipelines to extract, transform, and load data from various structured and unstructured data sources.
Work extensively with GCP services such as BigQuery, Cloud Storage, Dataflow, Pub/Sub, and Composer.
Implement data ingestion frameworks for batch and streaming pipelines.
Develop reusable and optimized data processing scripts in Python or Java.
Collaborate with data analysts, scientists, and application teams to ensure data quality, integrity, and accessibility.
Monitor, troubleshoot, and improve pipeline performance and reliability.
Ensure best practices in data governance, security, and compliance within GCP environment.
Required Skills & Qualifications:
Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.
5+ years of hands-on experience in data engineering and ETL development.
Strong experience with GCP data services (BigQuery, Dataflow, Cloud Storage, etc.).
Proficiency in Python or Java for data transformation, automation, and scripting.
Experience with SQL and working with relational databases (Oracle, MySQL, PostgreSQL, etc.) for data extraction.
Solid understanding of data modeling, schema design, and performance tuning.
Familiarity with Airflow, Cloud Composer, or other workflow orchestration tools.
Experience with Git, CI/CD, and version control tools is a plus.
Preferred Skills:
Experience with Apache Beam, Spark, or other distributed data frameworks.
Exposure to Kafka or Pub/Sub for real-time streaming data.
Knowledge of data warehousing concepts and analytics pipelines.

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