Data Engineer

Help a leading organization modernize and scale its cloud data platform. You will design and develop scalable data pipelines, build cloud-native data solutions on AWS, transform data using dbt, and enable analytics, reporting, and machine learning workloads across the enterprise.

Remote

6–12 Months

$50–$70/hr

• Design, build, and maintain scalable ETL/ELT pipelines
• Create and optimize data models in Snowflake
• Process large-scale datasets using PySpark and Apache Spark
• Build and maintain AWS-based data solutions
• Implement data quality, monitoring, and governance practices
• Collaborate with analytics, BI, and data science teams
• Optimize data warehouse performance and cost efficiency

4+ years of Data Engineering experience

Strong proficiency in Python, PySpark, SQL, and Apache Spark

Hands-on experience with Snowflake Data Cloud

Experience developing and maintaining dbt models and transformations

Strong knowledge of AWS services such as:

• AWS S3
• AWS Glue
• AWS Lambda
• AWS EMR
• AWS Redshift
• AWS IAM
• Amazon Cloud Watch

Experience building batch and streaming data pipelines

Strong understanding of dimensional modeling, star schema, and snowflake schema

Experience with workflow orchestration tools such as Airflow

Knowledge of CI/CD pipelines and Git-based version control

Experience with data quality, testing, and monitoring frameworks

Excellent communication and stakeholder management skills

Experience with Kafka or real-time streaming platforms

Experience with Terraform or Infrastructure as Code (IaC)

AWS Certification (Data Analytics, Solutions Architect, or Developer)

Experience supporting analytics and machine learning workloads

Exposure to Agile/Scrum environments