What are the responsibilities and job description for the Data Engineer position at QODE?
Role : Data Engineer
Location : Pittsburgh, PA / Cleveland, OH / Dallas, TX
Experience : 4–8 Years
Job Summary
We are seeking a highly motivated Data Engineer to join our growing team. The ideal candidate will have strong expertise in building scalable data pipelines, data integration frameworks, and distributed data processing solutions. The candidate should possess hands-on experience with Python, PySpark, Java, Kafka, Hadoop, REST APIs, and SQL, along with strong analytical and problem-solving skills.
This role requires collaboration with cross-functional teams to design, develop, and optimize enterprise data solutions that support business intelligence, analytics, and data-driven decision-making initiatives.
Key Responsibilities
Data Engineering & Development
Programming Languages
Location : Pittsburgh, PA / Cleveland, OH / Dallas, TX
Experience : 4–8 Years
Job Summary
We are seeking a highly motivated Data Engineer to join our growing team. The ideal candidate will have strong expertise in building scalable data pipelines, data integration frameworks, and distributed data processing solutions. The candidate should possess hands-on experience with Python, PySpark, Java, Kafka, Hadoop, REST APIs, and SQL, along with strong analytical and problem-solving skills.
This role requires collaboration with cross-functional teams to design, develop, and optimize enterprise data solutions that support business intelligence, analytics, and data-driven decision-making initiatives.
Key Responsibilities
Data Engineering & Development
- Design, develop, and maintain scalable data pipelines and ETL/ELT processes.
- Build and optimize large-scale data processing solutions using Python, PySpark, and Java.
- Develop data ingestion frameworks for structured and unstructured data sources.
- Integrate data from various systems through REST APIs, streaming platforms, and batch processing.
- Work with large datasets in distributed computing environments.
- Develop and support real-time and batch data processing solutions using Kafka and Hadoop ecosystem technologies.
- Implement scalable streaming data pipelines and event-driven architectures.
- Monitor and optimize data workflows for performance and reliability.
- Write complex SQL queries for data extraction, transformation, and analysis.
- Design and optimize database schemas and data models.
- Ensure data quality, consistency, and governance standards are maintained.
- Participate in Agile ceremonies including sprint planning, daily stand-ups, backlog grooming, and retrospectives.
- Use Jira for project tracking, issue management, and sprint execution.
- Collaborate with Data Architects, Data Scientists, Business Analysts, and Application Development teams.
- Work independently as well as within a collaborative team environment.
- Troubleshoot and resolve data-related issues across environments.
- Perform root cause analysis and implement long-term solutions.
- Support production deployments and ongoing maintenance activities.
Programming Languages
- Python
- PySpark
- Java
- Apache Kafka
- Hadoop Ecosystem
- SQL
- Data Warehousing Concepts
- ETL/ELT Development
- REST APIs
- Data Integration Frameworks
- Streaming and Batch Processing
- Jira
- Agile/Scrum
- Git Version Control
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- 4 years of experience in Data Engineering or Big Data development.
- Hands-on experience with Python, PySpark, Java, Kafka, Hadoop, REST APIs, and SQL.
- Strong analytical and problem-solving abilities.
- Ability to work effectively in both team-oriented and independent environments.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Knowledge of Spark optimization and performance tuning.