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Lead Data Engineer

Job

Nityo Infotech Corporation

Irvine, CA (In Person)

Full-Time

Posted 6 days ago (Updated 4 days ago) • Actively hiring

Expires 7/1/2026

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Job Description

Job Title:
Lead Data Engineer Location:
Irvine/Los Angeles (3 days hybrid)
Exerience:
10+ years overall, 3-4 years in specified technologies
Rate :
depends on evaluation, pls share your expected /hr rate
Job Description:
We are seeking a highly skilled and experienced Lead Data Engineer to join our dynamic team. The ideal candidate will have a strong background in data engineering, with extensive experience in Python , PySpark , AWS services , PostgreSQL , Apache Airflow and Docker . This role requires a professional with a proven track record of designing, implementing, and maintaining robust data pipelines and architectures.
Key Responsibilities:
Design and Develop Data Pipelines:
Create and maintain scalable data pipelines using Python and PySpark to process large volumes of data efficiently.
Cloud Integration :
Utilize AWS services (such as S3, CloudWatch, ECS, ECR, Lambda) to build and manage cloud-based data solutions.
Database Management:
Design, implement, and optimize PostgreSQL databases to ensure high performance and reliability.
Workflow Orchestration :
Use Apache Airflow to schedule and monitor complex data workflows.
Containerization:
Implement and manage Docker containers to ensure consistent and reproducible environments for data processing tasks.
Data Quality and Governance :
Ensure data quality, integrity, and security across all data pipelinesand storage solutions.
Collaboration:
Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs.
Mentorship:
Provide guidance and mentorship to junior data engineers and contribute to the continuous improvement of the team s skills and processes.
Qualifications:
Education :
Bachelor s or Master s degree in Computer Science, Engineering, or a related field.
Experience:
10+ years of overall experience in data engineering or related fields.
Technical Skills:
Proficiency in Python and PySpark. Extensive experience with AWS services (S3, CloudWatch, ECS, ECR, Secrets Manager, Cloud9 IDE). Strong knowledge of PostgreSQL and database optimization techniques. Hands-on experience with Apache Airflow for workflow orchestration. Proficiency in Docker for containerization.
Soft Skills:
Excellent problem-solving and analytical skills. Strong communication and collaboration abilities. Ability to work in a fast-paced, dynamic environment.
Preferred Qualifications:
Familiarity with CI/CD pipelines and DevOps practices. Knowledge of data warehousing concepts and ETL processes.