Big Data Developer

Posted 12 Hours Ago
Be an Early Applicant
3 Locations
In-Office
85K-160K Annually
Senior level
Artificial Intelligence • Hardware • Software • Semiconductor
The Role
Develop and maintain scalable big data applications, ETL/ELT pipelines, and real-time streaming solutions. Use Spark, Hadoop, Kafka, SQL, cloud platforms, and databases to integrate, transform, and process structured and unstructured data. Optimize performance, scalability, reliability, and data quality while implementing monitoring and security controls. Collaborate with engineers, scientists, and analysts, troubleshoot processing issues, and document technical solutions.
Summary Generated by Built In
Big Data Developer

Job Title: Big Data Developer
Job Locations: Austin, TX; Dallas, TX; Seattle, WA; Chicago, IL; New York, NY
Job Type: Full-Time
Experience Required: 2–8 Years
Work Mode: Remote / Hybrid / On-site, depending on employer
Estimated Annual Salary: $85,000–$160,000

Job Overview

We are seeking a skilled Big Data Developer with 2–8 years of experience to design, develop, and maintain scalable data processing systems. The ideal candidate will have strong programming skills and hands-on experience with big data technologies, distributed computing, cloud platforms, and data pipeline development.

Key Responsibilities
  • Design, develop, and maintain scalable big data applications and processing pipelines.

  • Build ETL/ELT workflows to process structured and unstructured data.

  • Develop data processing solutions using Apache Spark, Hadoop, and related technologies.

  • Write optimized SQL queries and data transformation scripts.

  • Integrate data from databases, APIs, and external sources.

  • Develop real-time data streaming solutions using Apache Kafka or similar technologies.

  • Work with AWS, Microsoft Azure, or Google Cloud Platform.

  • Optimize data processing performance, scalability, and reliability.

  • Collaborate with data engineers, data scientists, analysts, and software developers.

  • Implement data quality checks, security controls, and monitoring.

  • Troubleshoot data processing issues and maintain technical documentation.

Required Skills
  • Proficiency in Python, Java, Scala, or SQL.

  • Experience with Apache Spark, Hadoop, Hive, or Kafka.

  • Understanding of distributed computing and big data architecture.

  • Hands-on experience with ETL/ELT pipelines and data integration.

  • Knowledge of relational and NoSQL databases.

  • Familiarity with cloud data platforms and data warehouses.

  • Experience with data modeling, performance tuning, and data quality.

  • Strong analytical, problem-solving, and communication skills.

Experience Levels & Estimated Annual Salary

ExperienceEstimated Annual Salary (USD)2–3 Years$85,000–$105,0003–5 Years$100,000–$130,0005–8 Years$125,000–$160,000

Salary estimates are indicative and vary by employer, location, industry, and technical expertise.

Educational Qualifications
  • Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field preferred.

  • Equivalent professional experience, relevant certifications, and demonstrated technical skills may be considered.

Preferred Qualifications
  • Experience with AWS EMR, Azure Databricks, or Google Cloud Dataproc.

  • Familiarity with Apache Airflow, Delta Lake, or cloud data warehouses.

  • Knowledge of real-time streaming, data lakes, and distributed storage.

  • Experience with Git, Docker, CI/CD, and automated testing.

  • Understanding of data governance, security, and privacy standards.

Benefits
  • Competitive salary and performance-based incentives.

  • Health, dental, and vision insurance, where offered.

  • Paid time off and company holidays.

  • Professional development and certification opportunities.

  • Opportunities to work on large-scale data engineering projects.

How to Apply

Interested candidates can submit their updated resume highlighting relevant big data technologies, technical skills, certifications, and project experience.

Equal Opportunity Statement: We welcome qualified applicants from diverse backgrounds. Candidates must meet the applicable US work authorization requirements for the position.

Skills Required

  • Proficiency in Python, Java, Scala, or SQL
  • Experience with Apache Spark, Hadoop, Hive, or Kafka
  • Understanding of distributed computing and big data architecture
  • Hands-on experience with ETL/ELT pipelines and data integration
  • Knowledge of relational and NoSQL databases
  • Familiarity with cloud data platforms and data warehouses
  • Experience with data modeling, performance tuning, and data quality
  • Strong analytical, problem-solving, and communication skills
  • Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field
  • Equivalent professional experience, relevant certifications, and demonstrated technical skills may be considered
  • Experience with AWS EMR, Azure Databricks, or Google Cloud Dataproc
  • Familiarity with Apache Airflow, Delta Lake, or cloud data warehouses
  • Knowledge of real-time streaming, data lakes, and distributed storage
  • Experience with Git, Docker, CI/CD, and automated testing
  • Understanding of data governance, security, and privacy standards
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The Company
5 Employees
Year Founded: 2018

What We Do

EdgeQ develops 5G systems-on-chip for wireless infrastructure, combining connectivity and AI in a software-customizable, programmable platform. Its technology supports configurable 5G services and Open RAN deployments for enterprises, telecom operators and cloud providers, including base-station and edge-network use cases. The company’s mission is to make 5G more accessible through software-driven customization and bring cloud computing and data processing closer to where connectivity and data are used.

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