AWS Data Engineer

  • Torrance, CA
  • Posted 3 days ago | Updated moments ago

Overview

On Site
USD 65.00 - 65.00 per hour
Contract - W2
Contract - Independent

Skills

Management
Data flow
Accessibility
Pivotal
AIM
Decision-making
Design
Apache Spark
Performance tuning
Scalability
IaaS
Data processing
Business requirements
Business intelligence
Analytics
Documentation
Data integration
Workflow
Specification
Data governance
Policies
Computer science
Information Technology
Database design
Programming languages
Python
Amazon Web Services
Amazon S3
Electronic Health Record (EHR)
Amazon Redshift
PostgreSQL
Amazon RDS
Remote Desktop Services
PySpark
Data marts
Data warehouse
Extract
transform
load
System integration
Continuous integration
Continuous delivery
Database
Data
Data security
Privacy
Regulatory Compliance
Problem solving
Communication
Collaboration
Agile
Sprint
Planning
UPS
Mentorship
Attention to detail
Data quality
Data engineering
Finance
Accounting
Marketing
Legal
Customer support
Online training
Artificial intelligence
Insurance
.NET

Job Details

Description

Our client is a leader in their industry and seeking an AWS Data Engineer for a long term, multi-year assignment.

This role is hybrid, for 2 days/week onsite in Torrance, CA.

The IT Data Integration Engineer / Developer is tasked with the design, development, and management of data integration processes to ensure seamless data flow and accessibility across the organization. This role is pivotal in integrating data from diverse sources, transforming it to meet business requirements, and loading it into target systems such as data warehouses or data lakes. The aim is to support the organization's data-driven decision-making by providing high-quality, consistent, and accessible data.

Develop and Maintain Data Integration Solutions:

o Design and implement data integration workflows using AWS Glue/EMR, Lambda, Redshift

o Demonstrate proficiency in Pyspark, Apache Spark and Python for data processing large datasets

o Ensure data is accurately and efficiently extracted, transformed, and loaded into target systems.

Ensure Data Quality and Integrity:

o Validate and cleanse data to maintain high data quality.

o Ensure data quality and integrity by implementing monitoring, validation, and error handling mechanisms within data pipelines

Optimize Data Integration Processes:

o Enhance the performance, optimization of data workflows to meet SLAs, scalability of data integration processes and cost-efficiency on AWS cloud infrastructure.

o Identify and resolve performance bottlenecks, fine-tuning queries, and optimizing data processing to enhance Redshift's performance

o Regularly review and refine integration processes to improve efficiency.

Support Business Intelligence and Analytics:

o Translate business requirements to technical specifications and coded data pipelines

o Ensure timely availability of integrated data for business intelligence and analytics.

o Collaborate with data analysts and business stakeholders to meet their data requirements.

Maintain Documentation and Compliance:

o Document all data integration processes, workflows, and technical & system specifications.

o Ensure compliance with data governance policies, industry standards, and regulatory requirements.

Requirements

Bachelor's degree in computer science, information technology, or a related field. A master's degree can be advantageous.

7-10+ years of experience in data engineering, database design, ETL processes,

5+ in programming languages such as PySpark, Python

5+ years of experience with AWS tools and technologies (S3, EMR, Glue, Athena, RedShift, Postgres, RDS, Lambda, PySpark)

3+ years of experience of working with databases/ data marts/data warehouses

Proven experience in ETL development, system integration, and CI/CD implementation.

Experience in complex database objects to move the changed data across multiple environments

Solid understanding of data security, privacy, and compliance.

Excellent problem-solving and communication skills.

Display good communication skills to effectively collaborate with multi-functional teams

Participate in agile development processes including sprint planning stand-ups and retrospectives

Provide technical guidance and mentorship to junior developers

Attention to detail and a commitment to data quality.

Continuous learning mindset to keep up with evolving technologies and best practices in data engineering.

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