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Big Data Platform Engineer Jobs (NOW HIRING)

Prophecy Technologies

BIG DATA ENGINEER

Berkeley Heights, NJ · On-site

$58.25 - $77/hr

Big Data Engineer (Java,Spark, Hadoop, Ozone CH) Location: Berkeley Heights, NJ Role Overview: We ... data platforms. • Monitor and troubleshoot performance issues in large-scale clusters. • ...

FastTek

Platform Engineer

Dearborn, MI · On-site

Platform Engineer #1058624 * We are seeking a highly motivated full stack developer to join our ... Big Data Skills Preferred: * Design and Build Data Pipelines: Architect, develop, and maintain ...

IAMUS Consulting

(6835) Platform Engineer

San Antonio, TX · On-site +1

$132K - $172K/yr

Description We are looking for a Cloud Platform Engineer with experience in Cloud technology (AWS ... Prior experience or familiarity with DISA's Big Data Platform or other Big Data systems (e.g.

Veterans Sourcing Group, LLC

Big Data Engineer

Alpharetta, GA · On-site

$53 - $70/hr

Veterans Sourcing Group, LLC is seeking an experienced Big Data Engineer to join the CPS Data ... This role focuses on designing, enhancing, and governing data platform automation frameworks, with ...

Select Minds LLC

Big Data Engineer

Lansing, MI · On-site

$110K - $125K/yr

Ensure data quality, integrity, and governance across Big Data platforms. * Participate in ... Mentor junior engineers and contribute to technical best practices. Required Qualifications * 8+ ...

Syndicus, Inc.

Platform Engineer (7029)

Columbia, MD · Hybrid

$129K - $229K/yr

Experience with programming skills with Go. * Have a solid understanding of Linux systems, hosts ... Prior experience or familiarity with DISA's Big Data Platform or other Big Data systems (e.g.

IAMUS Consulting

(7029) Platform Engineer

Columbia, MD · On-site +1

$131K - $171K/yr

Description We are looking for a Cloud Platform Engineer with experience in Cloud technology (AWS ... Prior experience or familiarity with DISA's Big Data Platform or other Big Data systems (e.g.

IAMUS Consulting

(8019) Platform Engineer

San Antonio, TX · Hybrid

$150K - $195K/yr

We are looking for a Cloud Platform Engineer with experience in Cloud technology (AWS), programming ... Prior experience or familiarity with DISA's Big Data Platform or other Big Data systems (e.g.

IAMUS Consulting

(7031) Platform Engineer

Columbia, MD · On-site +1

$150K - $195K/yr

Description We are looking for a Cloud Platform Engineer with experience in Cloud technology (AWS ... Prior experience or familiarity with DISA's Big Data Platform or other Big Data systems (e.g.

IAMUS Consulting

(8019) Platform Engineer

San Antonio, TX · On-site +1

$150K - $195K/yr

Description We are looking for a Cloud Platform Engineer with experience in Cloud technology (AWS ... Prior experience or familiarity with DISA's Big Data Platform or other Big Data systems (e.g.

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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.

More about Big Data Platform Engineer jobs

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

For Big Data Platform Engineer jobs, the most frequently searched job titles are:

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.

Senior Data Platform Engineer

Dallas, TX • On-site

NewVision Software & Consultancy Pvt. Ltd
See more jobs at NewVision Software & Consultancy Pvt. Ltdexternal

$105K - $143K/yr

Other

Posted 25 days ago

Job description

Location: Dallas, TX (First 2 months hybrid)
Duration: 6 Months with possibility of Long Term Extension
We are looking for a Senior Data Platform Engineer with deep expertise in designing, optimizing, and managing enterprise-grade data ecosystems. This role requires mastery of database architecture, performance tuning, and transaction management, combined with hands-on experience in cloud-native platforms, big data frameworks, and advanced analytics pipelines. The ideal candidate will be comfortable working across distributed systems, modern data engineering tools, and collaborating with architects, DevOps, and business teams to deliver scalable, secure, and high-performing solutions.
KEY RESPONSIBILITIES
Database & System Architecture
  • Design and implement robust, scalable, and secure database architectures for transactional and analytical workloads.
  • Define partitioning strategies, indexing, and normalization for optimal performance and maintainability.
Performance Tuning & Optimization
  • Conduct advanced query optimization and execution plan analysis.
  • Implement proactive monitoring and troubleshooting for high-volume, mission-critical systems.
Cloud & Distributed Systems
Azure Service Fabric:
  • Deploy and manage microservices-based applications on Azure Service Fabric clusters.
  • Ensure high availability, fault tolerance, and scalability of distributed services.
  • Optimize communication patterns and stateful/stateless service design for data-intensive workloads.
Modern Data Engineering & Analytics
Azure Data Factory (ADF):
  • Design and orchestrate complex ETL/ELT pipelines for batch and streaming data.
  • Integrate diverse data sources into centralized data platforms.
Azure Databricks & Spark:
  • Build and optimize big data processing workflows using Apache Spark on Databricks.
  • Implement Delta Lake for ACID transactions on large-scale data lakes.
  • Develop scalable solutions for machine learning and advanced analytics.
Delta Tables:
  • Manage versioned data storage for reliability and reproducibility.
  • Optimize schema evolution and data compaction strategies.
Power BI (PBI):
  • Collaborate with BI teams to design semantic models and optimize data for reporting.
  • Ensure data pipelines deliver clean, consistent, and performant datasets for visualization.
Collaboration & Leadership
  • Work closely with architects, DevOps, and business stakeholders to align technical solutions with strategic objectives.
  • Provide mentorship and technical guidance to junior engineers and developers.
REQUIRED SKILLS & QUALIFICATIONS
Database Mastery
  • Advanced SQL, query optimization, partitioning, and transaction handling.
Performance Tuning
  • Proven ability to diagnose and resolve complex performance bottlenecks.
Azure Expertise
  • Hands-on experience with Azure Service Fabric, Azure Data Factory, Azure Databricks, and Azure Storage.
Big Data & Analytics
  • Strong knowledge of Spark, Delta Lake, and distributed data processing.
Data Visualization
  • Familiarity with Power BI and data modeling best practices.
Troubleshooting & Optimization
  • Ability to resolve issues across multi-tiered systems under pressure.
Cross-Functional Collaboration
  • Excellent communication and stakeholder management skills.
PREFERRED QUALIFICATIONS
  • Experience with CI/CD pipelines for data solutions.
  • Familiarity with data governance, security, and compliance frameworks.
  • Exposure to machine learning workflows and real-time streaming architectures.

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