Data Engineer: ETL & Snowflake on AWS (Mid-Level)

Ampcus, Inc; New York (NY); On-site; USD 110,000 - 180,000; Full time

Job summary

Ampcus Inc. is seeking a skilled Data Engineer to design, build, and manage scalable ETL pipelines for a centralized data lake and Snowflake data warehouse.

The role focuses on automating data ingestion, transformation, and aggregation workflows to enable reliable analytics and data-driven decision-making. In this intermediate-level position, you will design robust data pipelines, implement orchestration with ControlM and Airflow, and work with PySpark and Spark(Java) on AWS.

Qualifications

• Experience with data lake architectures and large-scale data processing.
• Hands-on experience with AWS services (S3, EC2, EMR, Glue).
• Proven expertise in building ETL pipelines for analytics and reporting.
• Snowflake data loading, transformations, and performance optimization.
• Experience with workflow automation and scheduling tools such as ControlM and Apache Airflow.
• Proficiency in PySpark for distributed data processing.
• Strong programming experience with Apache Spark using Java.
• Good understanding of data modeling, partitioning, and performance tuning concepts.
• Exposure to CI/CD practices for data pipelines.
• Experience in Agile or DevOps environments.

Responsibilities

• Design, develop, and maintain ETL pipelines for ingesting data into the data lake and Snowflake.
• Automate data processing, aggregation, and analytical workflows for availability and performance.
• Manage orchestration and scheduling of pipelines with ControlM and Airflow.
• Develop scalable data transformations using PySpark and Spark (Java).
• Work with large, structured and semi-structured datasets on AWS.
• Ensure data quality, integrity, and reliability across pipelines.
• Optimize pipelines for performance, cost, and scalability.
• Collaborate with analytics, data science, and business teams to define requirements.
• Monitor, troubleshoot, and resolve pipeline failures and bottlenecks.
• Follow best practices for data engineering, security, and documentation.

Skills

Data lake

AWS Services

ETL pipelines

Snowflake

Workflow automation

PySpark

Spark (Java)

Data modeling

Tools

ControlM

Apache Airflow

Job description

Ampcus Inc. is seeking a skilled Data Engineer to design, build, and manage scalable ETL pipelines for a centralized data lake and Snowflake data warehouse.

The role focuses on automating data ingestion, transformation, and aggregation workflows to enable reliable analytics and data-driven decision-making. In this intermediate-level position, you will design robust data pipelines, implement orchestration with ControlM and Airflow, and work with PySpark and Spark(Java) on AWS.