Torchora
Back to Home

Key Responsibilities and Required Skills for Big Data Apps Developer

💰 $90,000 - $140,000

Big DataSoftware DevelopmentData Engineering

🎯 Role Definition

The Big Data Applications Developer is responsible for designing, developing, and maintaining scalable big data applications and solutions that support organizational data processing and analytics initiatives. This role involves collaborating with data engineers, data scientists, and business stakeholders to build high-performance applications that leverage distributed computing frameworks, databases, and cloud technologies to drive data-driven decision-making.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Junior Data Engineer
  • Software Developer
  • ETL Developer

Advancement To:

  • Senior Big Data Developer
  • Data Solutions Architect
  • Lead Data Engineer

Lateral Moves:

  • Cloud Data Engineer
  • Data Analytics Specialist

Core Responsibilities

Primary Functions

  1. Design, develop, and deploy large-scale big data applications using distributed frameworks such as Hadoop, Spark, and Kafka.
  2. Write efficient, maintainable, and well-documented code for data ingestion, transformation, and processing pipelines.
  3. Collaborate with data scientists and analysts to translate business requirements into scalable technical solutions.
  4. Optimize big data applications for performance, reliability, and scalability.
  5. Implement data quality and validation checks to ensure accuracy and consistency across datasets.
  6. Integrate various data sources, including structured and unstructured data, into big data systems.
  7. Develop APIs and services to support application integration with big data platforms.
  8. Perform troubleshooting, debugging, and root-cause analysis of application issues.
  9. Participate in code reviews and maintain version control using Git or similar systems.
  10. Ensure adherence to coding standards, best practices, and security guidelines.
  11. Implement monitoring and logging for big data applications to maintain operational health.
  12. Design and implement data models for optimized storage and retrieval in big data environments.
  13. Assist in migrating legacy applications to modern big data platforms.
  14. Support cloud-based big data deployment using AWS, Azure, or GCP services.
  15. Automate workflows, batch processing, and real-time data streams for business use cases.
  16. Participate in agile development processes, including sprint planning, stand-ups, and retrospectives.
  17. Document technical designs, processes, and operational procedures.
  18. Stay updated on emerging big data technologies, frameworks, and tools.
  19. Collaborate with cross-functional teams to ensure seamless application integration.
  20. Support ad-hoc analytics requests and exploratory data investigations.

Secondary Functions

  • Conduct performance tuning and benchmarking of applications.
  • Mentor junior developers and provide guidance on best practices.
  • Assist in designing disaster recovery and backup strategies for big data applications.
  • Participate in internal knowledge-sharing sessions and technical training.

Required Skills & Competencies

Hard Skills (Technical)

  • Proficiency in big data frameworks such as Hadoop, Spark, and Kafka
  • Strong programming skills in Java, Scala, or Python
  • Experience with ETL tools and data pipeline orchestration
  • Knowledge of relational and NoSQL databases (SQL, MongoDB, Cassandra)
  • Cloud platform experience (AWS, Azure, or Google Cloud)
  • Familiarity with data modeling and schema design for big data
  • Experience with API development and integration
  • Strong understanding of distributed computing and parallel processing
  • Knowledge of performance tuning and optimization techniques
  • Experience with version control (Git) and CI/CD pipelines

Soft Skills

  • Strong problem-solving and analytical thinking
  • Effective communication with technical and non-technical stakeholders
  • Ability to work collaboratively in cross-functional teams
  • Time management and ability to prioritize tasks effectively
  • Adaptability to evolving technologies and project requirements
  • Detail-oriented and committed to high-quality work
  • Proactive attitude toward learning and innovation
  • Strong organizational skills and documentation abilities
  • Ability to mentor and guide junior team members
  • Critical thinking for troubleshooting complex systems

Education & Experience

Educational Background

Minimum Education:
Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or related field

Preferred Education:
Master’s degree in Data Science, Big Data Engineering, or Software Engineering

Relevant Fields of Study:

  • Computer Science / Software Engineering
  • Data Science / Analytics
  • Information Technology / Systems Engineering

Experience Requirements

Typical Experience Range:
3–5 years of experience in big data development or data engineering

Preferred:
5+ years of experience developing scalable big data applications and managing distributed data processing systems

Explore More Careers