Senior Data Engineer: Data Lakes, Pipelines & AWS Cloud

Dikshatek; United States; Remote; USD 28,000 - 44,000; Full time

Benefits offered by this job

Competitive salary

13th-month salary guarantee

Performance bonus

Premium health insurance

Extensive annual leave

Job summary

GFT is seeking a Senior Data Engineer with 8+ years of experience to design, maintain, and optimize data infrastructure and pipelines. You will work with data science and product teams to implement robust data models and scalable architectures.

The role emphasizes batch and real-time processing, Airflow workflows, and cloud services. You will ensure data quality, performance, and reliability while pursuing continuous improvement of the data platform.

Qualifications

• Minimum of 8 years of experience in data engineering.
• Experience building data lakes, pipelines, and metadata repositories.
• Collaborate with data science and product teams on data models.
• Experience with AWS services like Glue, EMR, EC2, S3, Lambda.
• CI/CD knowledge with Jenkins, CircleCI, or CodePipeline.
• Strong testing and quality assurance practices.

Responsibilities

• Design, maintain, and optimize data infrastructure and pipelines.
• Collaborate with data science teams on schemas and models.
• Develop batch and real-time data processing systems.
• Use Airflow and AWS Batch for workflow management.
• Ensure reliability with tests and monitoring.
• Drive continuous improvement of data platforms.

Skills

Unix environments

Cloud computing

Python (pandas, pyspark)

Git

Apache Airflow

Tools

Athena

Redshift

Vertica

Hive/Hadoop

AWS

Docker

Kubernetes

Job description

GFT is seeking a Senior Data Engineer with 8+ years of experience to design, maintain, and optimize data infrastructure and pipelines. You will work with data science and product teams to implement robust data models and scalable architectures.

The role emphasizes batch and real-time processing, Airflow workflows, and cloud services. You will ensure data quality, performance, and reliability while pursuing continuous improvement of the data platform.