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AWS Senior Data Engineer

Los Angeles area (4 days a week), CA, US • Posted 1 day ago • Updated 3 hours ago

Full Time

On-site

Fitment

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Job Details

Skills

LOS
FOCUS
ELT
Extraction
Recovery
Data Quality
Optimization
Scalability
SQL
Data Integration
Business Intelligence
Analytics
Reporting
Collaboration
Documentation
Workflow
Specification Gathering
Data Governance
Regulatory Compliance
Data Engineering
Database Design
Extract
Transform
Load
Data Warehouse
Amazon S3
Spectrum
Data Storage
Database
Data Processing
Apache Spark
Apache Hadoop
Java
Scala
Electronic Health Record (EHR)
Amazon Redshift
Amazon RDS
PySpark
Python
Continuous Integration
Continuous Delivery
Informatica
Cloud Computing
Artificial Intelligence
Amazon Web Services
Apache HTTP Server
Data Lake
JavaScript

LOS
FOCUS
ELT
Extraction
Recovery
Data Quality
Optimization
Scalability
SQL
Data Integration
Business Intelligence
Analytics
Reporting
Collaboration
Documentation
Workflow
Specification Gathering
Data Governance
Regulatory Compliance
Data Engineering
Database Design
Extract
Transform
Load
Data Warehouse
Amazon S3
Spectrum
Data Storage
Database
Data Processing
Apache Spark
Apache Hadoop
Java
Scala
Electronic Health Record (EHR)
Amazon Redshift
Amazon RDS
PySpark
Python
Continuous Integration
Continuous Delivery
Informatica
Cloud Computing
Artificial Intelligence
Amazon Web Services
Apache HTTP Server
Data Lake
JavaScript

Summary

Location: Los Angeles area (4 days a week)
W2 Candidates only
Long-term contract

Job Description

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.

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

#LI-JS2

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: sharpdec
Position Id: 53240
Posted 1 day ago

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