AWS Data Engineer

iSpace Inc
Torrance, CA, United States
4 days ago
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Role details

Contract type
Contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Working hours
Regular working hours
Job source

Tech stack

Training Data Airflow Amazon Web Services Amazon S3 Data Analysis Big Data Cloud Computing Cloud Database Continuous Delivery Data Architecture Data Validation Information Engineering
+35 more
Data Governance Data Integration Extract Transform Load (ETL) Data Systems Data Warehousing Database Design DevOps Distributed Computing Environment Apache Hadoop Identity and Access Management Data Intelligence Python (Programming Language) Machine Learning Performance Tuning Cloud Services Data Mesh Scala (Programming Language) Data Processing Apache Spark Informatica Cloud Generative AI Agentic-AI Amazon Relational Database Service Data Lakes Pyspark Deployment Automation AWS Lake Formation AWS Glue Integration Frameworks AWS Data Analytics Data Management Data Pipelines Amazon Elastic Mapreduce (EMR) Amazon Redshift Programming Languages

Job description

We are seeking a highly skilled AWS Data Engineer to design, build, and optimize scalable cloud-based data solutions. The ideal candidate will have extensive experience in AWS data engineering services, ETL/ELT development, data warehousing, and large-scale data processing. This role will focus on developing reliable, high-performance data pipelines that support analytics, reporting, and business intelligence initiatives while ensuring data quality, governance, security, and cost efficiency., Data Engineering & Pipeline Development

  • Design, develop, and maintain scalable data integration and processing solutions using AWS cloud technologies.
  • Build and optimize ETL/ELT pipelines utilizing AWS Glue, EMR, MWAA (Airflow), Lambda, Redshift, and related services.
  • Develop data processing frameworks using Python, PySpark, and Apache Spark to efficiently manage large datasets.
  • Implement robust, production-ready data pipelines that support enterprise analytics and reporting needs.
  • Translate business requirements into technical specifications and scalable data engineering solutions.

Data Quality & Governance

  • Develop and implement data validation, monitoring, and error-handling frameworks.
  • Ensure data accuracy, integrity, consistency, and reliability across data platforms.
  • Implement security and governance controls using AWS IAM and AWS Lake Formation.
  • Support compliance with organizational data governance, security, and regulatory standards.

Performance Optimization

  • Optimize data workflows for performance, scalability, reliability, and cost efficiency.
  • Identify and resolve bottlenecks in data processing and data warehouse environments.
  • Fine-tune Redshift queries, workloads, and architectures to improve overall system performance.
  • Continuously review and enhance data integration processes to meet service-level agreements (SLAs).

Analytics & Business Support

  • Partner with business stakeholders, analysts, and data teams to deliver trusted, timely datasets.
  • Support business intelligence and advanced analytics initiatives by providing high-quality integrated data.
  • Collaborate across teams to improve data accessibility and usability throughout the organization.

Documentation & DevOps

  • Maintain technical documentation, architecture diagrams, and operational procedures.
  • Leverage CI/CD pipelines and DevOps best practices for automated deployment and management of data solutions.
  • Support production releases, troubleshooting, monitoring, and ongoing maintenance activities.

Requirements

Applicants must be authorized to work in the U.S. without current or future employer sponsorship. Sponsorship for employment visas is not available for this role., * 7+ years of experience in Data Engineering, ETL development, data modeling, database design, and data warehousing.

  • 5+ years of hands-on experience with AWS data technologies, including:

  • Amazon S3
  • Amazon EMR
  • AWS Glue
  • Amazon Athena
  • Amazon Redshift
  • Amazon RDS
  • Redshift Spectrum
  • AWS MWAA (Airflow)

5+ years of experience with Python, PySpark, Scala, or similar programming languages.

2+ years of experience implementing CI/CD pipelines and DevOps practices for data engineering solutions.

2+ years of hands-on experience with AWS IAM and AWS Lake Formation, including:

  • IAM roles and policies
  • Access management
  • Data lake security
  • Governance controls

Strong expertise in distributed data processing technologies, including Apache Spark, Hadoop, and cloud-based data lake architectures.

Experience with Informatica Intelligent Data Management Cloud (IDMC) / Informatica Cloud.

Strong understanding of data warehouse concepts, performance tuning, and cloud-native data architectures.

Preferred Qualifications

  • Experience implementing Agentic AI or Generative AI solutions within data engineering environments.
  • Experience building AI-ready data platforms and supporting machine learning workloads.
  • Knowledge of modern data architecture patterns, including data lakes, lakehouses, and data mesh concepts.
  • AWS certifications such as AWS Certified Data Engineer, AWS Certified Solutions Architect, or related credentials.

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