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Big Data Platform Engineer Jobs (NOW HIRING)

Cymertek Corporation

Big Data Engineer

Reston, VA · On-site

$58 - $76.75/hr

Big Data Engineer LOCATIONReston, VA 20190 CLEARANCETS/SCI Full Poly (Please note this position ... Data Platform Engineer, Cloud Data Engineer, Database Engineer, Data Infrastructure Engineer ...

Inficare Technologies

Platform Engineer

Phoenix, AZ · On-site

Job Title: Platform Engineer Location: Phoenix, AZ (Hybrid - 3 days onsite) Job Type: Contract ... Manage distributed messaging or big data platforms as needed (Kafka or Hadoop) * Ensure platform ...

ClifyX

Big Data Senior Engineer

Phoenix, AZ · On-site

$55.25 - $73.25/hr

The role involves hands-on experience with Big Data platforms and developing cloud-based solutions, particularly with AWS. Responsibilities : • Senior Engineer with Hands on Experience in Big Data ...

Real Soft, Inc.

Platform Engineer (1924)

Columbia, MD · On-site

We are looking for a Cloud Platform Engineer with experience in Cloud technology (AWS), Python ... Big Data / Cloud technology. As a result, the candidate will be expected to work autonomously ...

Cymertek Corporation

Big Data Engineer

Chantilly, VA · On-site

$57 - $75.50/hr

Big Data Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this ... Data Platform Engineer, Cloud Data Engineer, Database Engineer, Data Infrastructure Engineer ...

Cymertek

Big Data Engineer

Annapolis Junction, MD · On-site

$57 - $75.25/hr

Big Data Engineer LOCATION Annapolis Junction, MD 20701 CLEARANCE TS/SCI Full Poly (Please note ... Data Platform Engineer, Cloud Data Engineer, Database Engineer, Data Infrastructure Engineer ...

Cymertek Corporation

Big Data Engineer

Aurora, CO · On-site

$56.75 - $75.25/hr

Big Data EngineerLOCATION Aurora, CO 80014 CLEARANCE TS/SCI Full Poly (Please note this position ... Data Platform Engineer, Cloud Data Engineer, Database Engineer, Data Infrastructure Engineer ...

Real Soft, Inc.

Platform Engineer (2391)

Columbia, MD · On-site

We are looking for a Cloud Platform Engineer with experience in Cloud technology (AWS), Python ... Big Data / Cloud technology. As a result, the candidate will be expected to work autonomously ...

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Big Data Platform Engineer information

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How much do big data platform engineer jobs pay per hour?

As of Sep 12, 2026, the average hourly pay for big data platform engineer in the United States is $62.98, according to ZipRecruiter salary data. Most workers in this role earn between $53.61 and $70.91 per hour, depending on experience, location, and employer.

What is a big data platform engineer?

Big Data Platform Engineers are technology professionals who design, build, and maintain large-scale data processing systems. They work with tools and frameworks such as Hadoop, Spark, and cloud-based solutions to manage, process, and analyze vast amounts of structured and unstructured data. Their role involves ensuring data pipelines are reliable, scalable, and secure, supporting data scientists and analysts in extracting valuable insights from big data. They also optimize system performances and troubleshoot issues related to data storage and processing. Overall, they play a crucial role in enabling data-driven decision-making within organizations.

What are the key skills and qualifications needed to thrive as a big data platform engineer?

To thrive as a Big Data Platform Engineer, you need strong expertise in distributed computing, data architecture, and programming languages like Java, Python, or Scala, typically supported by a degree in computer science or a related field. Familiarity with big data tools and frameworks such as Hadoop, Spark, Kafka, and cloud platforms (e.g., AWS, Azure) as well as certifications like Cloudera or AWS Big Data are often required. Problem-solving, adaptability, and effective communication are essential soft skills for collaborating with cross-functional teams and addressing complex data challenges. These skills and qualities are crucial for designing, optimizing, and maintaining robust data solutions that drive business insights and innovation.

What are some typical challenges a big data platform engineer faces when integrating new data sources into an existing platform?

Big Data Platform Engineers often encounter challenges like ensuring data compatibility, maintaining data quality, and minimizing disruption to ongoing operations when integrating new sources. They need to address issues such as data format inconsistencies, varying data latency, and scaling ingestion pipelines to handle increased loads. Collaboration with data architects, data scientists, and business stakeholders is essential to align integration efforts with organizational needs and compliance requirements. Effective troubleshooting and automation can help streamline the integration process and maintain platform stability.

What is the difference between Big Data Platform Engineer vs Data Engineer?

AspectBig Data Platform EngineerData Engineer
Primary FocusDesigning, building, and maintaining big data infrastructure and platformsDeveloping data pipelines, ETL processes, and managing data storage
Skills & CertificationsBig data technologies (Hadoop, Spark), cloud platforms, scriptingSQL, Python, data modeling, ETL tools
Work EnvironmentData infrastructure teams, cloud environments, large-scale data systemsData teams, analytics, and application development environments
Industry UsageTech companies, finance, healthcare with large data needsAny industry requiring data integration and analytics

While both roles involve working with data, Big Data Platform Engineers focus on building and maintaining the infrastructure for big data processing, whereas Data Engineers develop data pipelines and manage data flow for analysis. Both roles often collaborate but serve different core functions within data ecosystems.

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What are popular job titles related to Big Data Platform Engineer jobs?

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Big Data Platform Engineer jobs near you
Infographic showing various Big Data Platform Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $131,001 per year, or $63 per hour.

Platform Engineer - Big Data

Rockville, VA • On-site

Noblesoft Technologies
Software Development • 51 - 200 employees
Learn more about Noblesoft Technologiesexternal

$51.75 - $68.25/hr

Contractor

Re-posted 15 days ago

Job description

Role: Senior Platform Engineer - Big Data (AWS | EMR | EKS) 

Location: Rockville, MD, Tysons Corner, VA or Woodbridge, NJ or Jersey City, NJ (3 days onsite per week)

Duration: 6 months (long-term extensions)

 

Notes:

 Senior Platform Engineer – Big Data (AWS | EMR | EKS)

  • Build and modernize a large‑scale AWS big data platform (EMR, S3, Athena, Trino) supporting enterprise analytics
  • Help drive platform evolution toward cloud‑native, containerized workloads on AWS EKS (Kubernetes)
  • Work at the intersection of software engineering, big data, and platform engineering — not ETL‑only
  • Design and operate Spark‑based data workloads, optimizing performance, reliability, and cost
  • Implement CI/CD and Infrastructure as Code (Terraform / CloudFormation) for data platforms
  • Ideal for engineers with a strong backend or platform background who’ve grown into big data

Job Description:

Overview

We are seeking a Senior Platform Engineer with deep Big Data experience to help design, operate, and modernize a large‑scale data platform on AWS. This role goes beyond traditional ETL or pipeline development — it is focused on building and evolving the underlying data platform that supports analytics, reporting, and future AI/ML use cases.

The current environment is built primarily on AWS EMR and S3, with a strong query layer using Athena and Trino. The team is actively modernizing the platform and evaluating AWS EKS (Kubernetes) as part of a shift toward more cloud‑native, containerized data workloads.

This role is ideal for an engineer with a software or platform engineering background who moved into big data, rather than a pure ETL developer.

Key Responsibilities

  • Design, build, and operate scalable big data platforms on AWS, with S3 as the core data lake.
  • Develop and optimize Spark‑based workloads on EMR, including performance tuning and cost optimization.
  • Support and enhance federated query engines such as Athena and Trino for large‑scale analytics.
  • Contribute to the modernization of the data platform, including evaluation and adoption of Kubernetes/EKS for data services and workloads.
  • Build and operate data services and platform components using containerized deployments (Docker + EKS).
  • Implement and maintain Infrastructure as Code using Terraform and/or CloudFormation.
  • Design and support CI/CD pipelines for data and platform workloads.
  • Partner with data engineers, analytics teams, and stakeholders to ensure the platform is reliable, performant, and extensible.
  • Monitor and troubleshoot platform issues across clusters, pipelines, and query engines using CloudWatch and related tooling.
  • Continuously evaluate new technologies and propose improvements to the overall data architecture.

Required Qualifications

  • 8+ years of experience in Big Data, Platform Engineering, or Data Engineering roles.
  • Strong hands‑on experience with AWS, including:
    • EMR
    • S3
    • Athena
    • AWS Glue / Glue Data Catalog
  • Solid experience with Spark (PySpark or Scala) and distributed data processing.
  • Strong SQL skills, particularly with large datasets (Athena, Trino, Presto, etc.).
  • Experience with Docker and containerized applications.
  • Working knowledge of Kubernetes, with exposure to AWS EKS strongly preferred.
  • Experience implementing CI/CD pipelines (Jenkins, GitHub Actions, or similar).
  • Infrastructure as Code experience using Terraform and/or CloudFormation.
  • Strong scripting and programming skills (Python preferred).
  • Ability to think at a platform and architecture level, not just task execution.

Nice to Have

  • Experience running Spark on Kubernetes (EKS).
  • Trino/Presto performance tuning experience.
  • Experience preparing data platforms for AI/ML workloads.
  • Observability tooling experience (CloudWatch, Grafana, Prometheus).
  • Background as a software engineer before moving into big data.