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AWS Senior Data Engineer

Sharp DecisionsTorrance, CA🇺🇸United StatesPosted 17 Aug 2026

Why This Role Stands Out

Advance your career as a Senior Data Engineer with Sharp Decisions, where you'll gain valuable experience optimizing scalable data pipelines on AWS and contribute to impactful analytics. This hybrid role is perfect for experienced professionals skilled in AWS data services, PySpark, and Redshift who thrive on solving complex data challenges and driving innovation. Apply today to join a dynamic team and shape the future of data at Sharp Decisions!

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Job Summary

Location: Torrance CA (4 days a week)

We are seeking a Data Engineer with 5+ years of experience in data engineering, ETL, data warehousing, and database design. The ideal candidate will have strong hands-on experience with AWS data services, PySpark/Spark, Python, Airflow, and Redshift, with a focus on designing, developing, optimizing, and supporting scalable data pipelines.

Key Responsibilities
Data Integration & Pipeline Development
  • Design, develop, and maintain data integration workflows using AWS Glue, EMR, MWAA/Airflow, Lambda, and Redshift.
  • Build scalable ETL/ELT pipelines for processing large datasets.
  • Use Python, PySpark, and Apache Spark for data transformation and processing.
  • Ensure accurate and efficient extraction, transformation, and loading of data into target systems.
  • Design and support data pipelines throughout the development and production lifecycle.
Data Quality & Integrity
  • Validate, cleanse, and transform data to maintain high levels of data quality.
  • Implement monitoring, validation, error handling, and recovery mechanisms within data pipelines.
  • Identify and resolve data quality and integration issues.
Performance & Cloud Optimization
  • Optimize data workflows for performance, scalability, reliability, SLAs, and cost efficiency within AWS.
  • Identify and resolve pipeline and processing bottlenecks.
  • Tune SQL queries and optimize Amazon Redshift performance.
  • Continuously review and improve existing data integration processes.
Business Intelligence & Analytics
  • Translate business requirements into technical specifications and data pipelines.
  • Ensure timely availability of integrated data for analytics and reporting.
  • Collaborate with data analysts, business stakeholders, and technical teams to understand and deliver data requirements.
Documentation & Compliance
  • Document data pipelines, workflows, architecture, technical specifications, and system processes.
  • Follow data governance, security, compliance, and regulatory requirements.
Required Qualifications
  • 5+ years of experience in data engineering, database design, ETL, and data warehousing.
  • 3+ years of experience with AWS data services, including:
    • AWS S3
    • AWS EMR
    • AWS Glue
    • AWS Athena
    • Amazon Redshift
    • Amazon RDS
    • Redshift Spectrum
    • AWS MWAA / Airflow
  • 2+ years of experience with CI/CD tools and practices.
  • Strong knowledge of data storage, data lakes, databases, and distributed data-processing frameworks.
  • Hands-on experience with Apache Spark, PySpark, or Hadoop.
  • 3+ years of programming experience with Python, Java, or Scala.
  • Experience designing, developing, and supporting production data pipelines.
Primary Skills

AWS EMR | AWS Glue | Airflow/MWAA | Apache Iceberg | Amazon Redshift | Amazon RDS | PySpark | Python | CI/CD

Nice to Have
  • Informatica Cloud / IDMC experience.
  • Agentic AI / Amazon Kiro experience.
  • Experience with Apache Iceberg and modern data lake architectures.

#LI-JS2

Skills

SQL
Scala
AWS
ETL
Airflow
Apache
Apache Spark
Hadoop
Java
Python
Redshift

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