Data Engineer – Intermediate

Ampcus Inc.•New York, NY

1d•Onsite

About The Position

We are seeking a skilled Data Engineer to design, build, and manage scalable ETL pipelines supporting 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.

Requirements

Strong experience with data lake architectures and large-scale data processing.
Hands-on experience with AWS services (e.g., S3, EC2, EMR, Glue, or related).
Proven expertise in building ETL pipelines for analytics and reporting use cases.
Solid working knowledge of Snowflake, including data loading, transformations, and performance optimization.
Experience with workflow automation and scheduling tools such as Control‐M 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.

Nice To Haves

Exposure to CI/CD practices for data pipelines.
Experience working in Agile or DevOps environments.

Responsibilities

Design, develop, and maintain robust ETL pipelines for ingesting data into the enterprise data lake and Snowflake environment.
Automate data processing, aggregation, and analytical workflows to improve data availability and performance.
Implement and manage orchestration and scheduling of data pipelines using Control‐M and Apache Airflow.
Develop scalable data transformation logic using PySpark and Apache Spark (Java).
Work with large, structured and semi-structured datasets on AWS infrastructure.
Ensure data quality, integrity, and reliability across data pipelines.
Optimize data pipelines for performance, cost, and scalability.
Collaborate with analytics, data science, and business teams to understand data requirements.
Monitor, troubleshoot, and resolve pipeline failures and performance bottlenecks.
Follow best practices for data engineering, security, and documentation.