Data Engineer AWS SQL PySpark Python S3 Glue Iceberg Snowflake Redshift Athena Talend dbt Data Architecture

Acunor Infotech

Erie, PA, United States

5 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Amazon Web Services Amazon S3 Big Data Continuous Integration Data Architecture Information Engineering Data Infrastructure Data Integration Extract Transform Load (ETL) Identity and Access Management Python (Programming Language) Meta-Data Management

+14 more

Cloud Services SQL Databases Data Streaming Talend Sql Optimization Snowflake IT Architecture Amazon Virtual Private Cloud (VPC) Git Pyspark AWS Glue Data Management Splunk Data Pipelines

Job description

We are seeking a Senior Full-Stack Data Engineer with deep expertise in AWS, SQL, PySpark, and Python to architect, develop, and optimize next-generation cloud data platforms. The ideal candidate will have experience with large-scale data infrastructure and modern data engineering technologies. Key Responsibilities

Design and develop scalable AWS cloud data platforms.
Build and optimize ETL/ELT pipelines using SQL, PySpark, and Python.
Work with petabyte-scale data infrastructure and modern data architectures.
Develop solutions using AWS Glue, S3, Iceberg, Snowflake, Redshift, and Athena.
Support data integration, streaming, metadata management, and data quality.
Implement CI/CD and version control using Git.
Provide technical leadership, architecture guidance, and mentoring.

Requirements

10 15 years of Data Engineering/Data Architecture experience.
Strong AWS experience including S3, IAM, and VPC.
Advanced SQL, PySpark, and Python.
Experience with Talend, dbt Core, Iceberg, AWS Glue Catalog.
Experience with Snowflake, Redshift, and Athena.
Experience with AWS streaming services and Splunk.
Strong understanding of ETL/ELT, metadata management, and cloud-native data platforms.

Preferred Qualifications