Amazon S3 Engineer

Location: Charlotte, NC

Salary: $120,000.00 USD Annually - $130,000.00 USD Annually

Description:

Job Title: Senior Amazon Data Engineer

Experience: 10+ Years

Location: Charlotte, NC or Plano, TX (Onsite)

Employment: Fulltime

Job Summary

We are seeking an experienced Senior Amazon Data Engineer to design, develop, and optimize large-scale data pipelines within a cloud-based data platform. The ideal candidate will have strong expertise in Amazon S3, AWS Data Engineering, PySpark, SQL, and ETL/ELT frameworks, along with hands-on experience in banking and payments data domains.

This role involves building reliable, scalable data solutions, ensuring high data quality and integrity, and working closely with cross-functional teams in a Cloudera-based big data environment.

Key Responsibilities

Design, develop, and execute end-to-end data pipelines and validation test cases to ensure data accuracy, integrity, and quality.

Build, implement, and optimize ETL/ELT workflows leveraging Amazon S3 for scalable data storage, retrieval, and processing.

Develop scripts and automation for data movement between Amazon S3 and on-prem or cloud platforms using PySpark, Shell scripting, or similar tools.

Utilize Amazon S3 advanced features such as:

Versioning

Lifecycle policies

Access control (IAM policies, bucket policies)

Server-side encryption

Monitor, troubleshoot, and optimize pipeline performance to ensure high availability and reliability.

Collaborate with data engineers, developers, analysts, and business stakeholders to resolve data-related issues efficiently.

Validate and manage HiveQL, HDFS file structures, and data processing within Hadoop/Spark environments.

Work within a metadata-driven ETL framework and batch/job scheduling systems.

Create and maintain technical documentation, ensuring adherence to data engineering best practices.

Support data governance, data quality checks, and compliance requirements within a regulated banking environment.

Required Skills & Qualifications

Technical Skills

Primary Skill: Amazon Data Engineering

Secondary Skills:

AWS Data Engineering

Amazon S3 (storage, lifecycle management, security, automation)

PySpark

SQL

Shell Scripting

Autosys (job scheduling)

Strong hands-on experience with Hadoop, Spark, Hive, and HDFS

Experience working with Oracle databases

Strong understanding of data warehousing concepts, data transformation, and data quality frameworks

Experience in Cloud Storage and AWS ecosystems

Tools & Platforms

Amazon S3

PySpark

SQL

Oracle

Autosys

Cloudera Platform

Domain Experience

Banking domain experience is required

Payments domain experience is preferred

Soft Skills

Strong analytical and problem-solving skills

Excellent verbal and written communication skills

Ability to collaborate effectively with cross-functional and offshore teams

Detail-oriented with a strong focus on data accuracy and quality

Preferred Qualifications

Experience with metadata-driven ETL processes

Exposure to large-scale distributed data processing

Familiarity with enterprise data governance and compliance standards

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Contact:

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