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Amazon Data Engineer Jobs in Florida (NOW HIRING)

Raymondjames

Lead Cloud Data Engineer

Saint Petersburg, FL · Hybrid

$96K - $127K/yr

Integrate data from various sources into Amazon Redshift, ensuring data quality and consistency ... Mentor and guide junior engineers on the team. * Continuously explore new AWS services and ...

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Amazon Data Engineer information

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$33.3K

$96.9K

$132.6K

How much do amazon data engineer jobs pay per year?

As of Jul 15, 2026, the average yearly pay for amazon data engineer in Florida is $96,936.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,600.00 and $102,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Amazon Data Engineer position, and why are they important?

To thrive as an Amazon Data Engineer, you need strong proficiency in data modeling, ETL development, SQL, and programming languages such as Python or Java, typically accompanied by a degree in computer science or a related field. Familiarity with AWS cloud services (like Redshift, S3, and Glue), big data tools, and relevant certifications such as AWS Certified Data Analytics are highly valued. Strong problem-solving skills, effective communication, and the ability to work collaboratively in cross-functional teams set standout candidates apart. These skills and qualities ensure data is accurately managed, integrated, and made accessible for analytics and business decisions in Amazon's complex environment.

What types of projects and data challenges do Amazon Data Engineers typically work on in their day-to-day roles?

As an Amazon Data Engineer, you can expect to work on projects involving the design, development, and maintenance of large-scale data pipelines and data warehouses. Common challenges include optimizing data flows for efficiency, handling massive and complex datasets, and ensuring data quality and integrity across various sources. You'll frequently collaborate with data scientists, analysts, and other engineering teams to create scalable solutions that support business intelligence and machine learning initiatives. The fast-paced environment provides opportunities to solve unique technical problems and drive data-driven decision-making across Amazon’s diverse businesses.

What is an Amazon Data Engineer job?

An Amazon Data Engineer is responsible for designing, building, and maintaining data infrastructure to support business intelligence and analytics. They work with large-scale datasets, optimize data pipelines, and ensure efficient data processing. Engineers collaborate with data scientists, analysts, and software teams to enable data-driven decision-making. Key skills include SQL, Python, ETL development, and experience with AWS services like Redshift, S3, and Glue.

What are the most commonly searched types of Amazon Data Engineer jobs in Florida? The most popular types of Amazon Data Engineer jobs in Florida are:
What are popular job titles related to Amazon Data Engineer jobs in Florida? For Amazon Data Engineer jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Amazon Data Engineer jobs in Florida look for? The top searched job categories for Amazon Data Engineer jobs in Florida are:
What cities in Florida are hiring for Amazon Data Engineer jobs? Cities in Florida with the most Amazon Data Engineer job openings:
Amazon Data Engineer jobs near you
Information Technology_USA - USA_Engineer

Information Technology_USA - USA_Engineer

Real Soft, Inc.

Jacksonville, FL • On-site

$106K - $127K/yr

Contractor

Re-posted 13 days ago

Job description

ALL CAPS, NO SPACES B/T UNDERSCORES PTN_US_GBAMSREQID_
Candidate BeelineID i.e. PTN_US_9999999_SKIPJOHNSON0413
MSP Owner: Thomas Hodges
Targeted - -hr
REQUIREMENT_CITY - Malvern, PA
REQUIREMENT_ID-10695673
Role Name - Senior Data Engineer - AWS & Python
ROLE_DESCRIPTION -
Build and maintain event-driven data pipelines using AWS services such as Kinesis, MSK/Kafka, Lambda, Step Functions, SQS/SNS, and Glue/EMR.
Develop ETL/ELT workflows using Python and PySpark, ensuring performance, scalability, and cost efficiency.
Implement and optimize Spark-based data transformations, partitioning strategies, and data processing frameworks.
Design and manage data lake and warehouse structures using S3, Glue Catalog, Athena, and/or Redshift.
Build streaming solutions with checkpointing, stateful transformations, idempotency, and schema evolution.
Ensure high standards of data quality, observability, monitoring, and alerting (CloudWatch, Datadog, etc.).
Implement data security best practices including IAM, encryption (KMS), networking, and governance.
Create reusable frameworks, internal libraries, and CI/CD pipelines for automated deployments.
Collaborate with data scientists, analysts, and business teams to deliver well-modeled, reliable datasets.
Lead design reviews, mentor junior engineers, and contribute to engineering best practices.
Required Qualifications
Overall 8+ yrs of experience
5+ years of professional experience in Data Engineering.
Experience of working on Java is an advantage
Strong expertise in Python and PySpark for large-scale data processing.
Advanced hands-on experience with AWS (S3, Glue, EMR, Lambda, Step Functions, Kinesis/MSK, DynamoDB, Athena, Redshift).
Deep experience building event-driven and streaming data pipelines.
Strong SQL experience for analytical and ETL workloads.
Hands-on experience with workflow orchestration tools such as Airflow or Step Functions.
Experience with CI/CD, Git, and Infrastructure-as-Code (Terraform or CloudFormation).
Strong understanding of distributed systems, Spark performance tuning, data modeling, and cloud cost optimization.
Knowledge of data security, encryption, networking, and compliance best practices in cloud environments
Skills: Digital : Python~Digital : Amazon Web Service(AWS) Cloud Computing~Digital : PySpark~Core Java
Experience Required: 6-8, Project Code :

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