Data Engineer

Drevol LLC

Malvern, PA, United States

about 1 month ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

7 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Airflow Amazon Web Services Amazon S3 Apache HTTP Server Cloud Database Continuous Integration Information Engineering Extract Transform Load (ETL) Data Systems Distributed Computing Environment Github Python (Programming Language)

+18 more

Cloud Services SQL Databases Enterprise Data Management Data Ingestion Snowflake Apache Spark Git Cloudformation Data Lakes Pyspark Information Technology AWS Glue AWS Data Analytics Apache Kafka Data Management Terraform Data Pipelines Databricks

Job description

We are seeking an experienced Data Engineer with strong expertise in Python, PySpark, AWS Glue, and AWS data services to build and support scalable ETL/ELT pipelines for enterprise financial and data platforms. The ideal candidate will have hands-on experience with cloud-based data lakes, distributed data processing, CI/CD, and production support., * Design, develop, and optimize ETL/ELT pipelines using Python, PySpark, and AWS Glue.

Build scalable data ingestion and transformation solutions for enterprise data platforms.
Develop cloud-native data lake solutions and ensure data quality and reliability.
Implement CI/CD pipelines using GitHub Actions.
Support production environments, troubleshoot pipeline issues, and optimize performance.
Collaborate with business and technical teams in an Agile environment.

Requirements

Bachelor’s degree in Computer Science or related field.
7+ years of Data Engineering experience.
Strong experience with Python, SQL, Apache Spark (PySpark), and AWS Glue.
Hands-on experience with AWS S3, Athena, Lambda, Step Functions, and EventBridge.
Experience building enterprise ETL/ELT pipelines and cloud data platforms.
Knowledge of CloudFormation or Terraform, Git, and GitHub Actions.
Strong understanding of data modeling and distributed data processing.
Excellent communication and problem-solving skills., * Financial Services or Asset Management experience.
Snowflake or Databricks.
Apache Iceberg, Delta Lake, or Hudi.
Airflow, Kafka, or Kinesis.
AWS Certifications., This role is ideal for a Data Engineer with strong AWS and Spark expertise who enjoys building scalable, high-performance data solutions in a cloud environment.