Full Stack Data Engineer

rockITdata, a veteran, minority, and woman-owned small business certified by the NWBOC, is a full-service consulting provider that specializes in providing management and IT services. We help companies build efficiencies, decrease cost, and drive better outcomes. We achieve these goals by leveraging industry leading cloud based artificial intelligence and machine learning technologies.
We bring four distinct offerings to Commercial; Federal; and State, Local, and Education clients.

• Management Consulting: We provide advisory services to design, manage, and execute lasting change, leveraging trusted relationships and industry expertise in strategy, organizational transformation, operations, operational excellence, innovation, risk and compliance, human capital, and workforce optimization.
• AI, Data & Analytics: Deploying advanced AI and ML solutions, business analytics to extract actionable insight, data engineering for data warehousing, real-time processing and integrated quality data and platform architecture focusing on cloud and hybrid solutions, security and solution selection and integration. 
• IT Transformation: Delivering technology services, covering application lifecycle management, CRM implementation, systems integration, rockITCX contact center solutions, product resale, and IT infrastructure management. Our approach ensures seamless operations and enhanced customer engagement, optimizing technology investments for diverse businesses. 
• Mission Support: Specializing in System Engineering Technical Assistance and operations support services to streamline system integration and optimization while ensuring operational excellence for modern enterprises.

We are seeking a talented and experienced Full Stack Data Engineer to join our team. The ideal candidate will have a strong background in both data engineering and software development, with expertise in building end-to-end data solutions. This role offers an exciting opportunity to work on diverse data projects and contribute to the development of innovative data-driven applications. This is a Remote position.
Key Responsibilities
 

• Data Ingestion and Integration:
  
  • Design and implement scalable data ingestion pipelines to efficiently collect and process data from various sources.
  • Integrate data from different systems and platforms to create unified datasets for analysis and reporting.
• Data Storage and Management:
  
  • Develop and maintain data storage solutions such as data lakes, data warehouses, and NoSQL databases.
  • Optimize data storage and retrieval mechanisms for performance, scalability, and cost-effectiveness.
• Data Processing and Transformation:
  
  • Implement data processing workflows for cleaning, transforming, and enriching raw data into usable formats.
  • Apply data transformation techniques such as ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes.
• Data Modeling and Optimization:
  
  • Design and implement data models to support analytical and reporting requirements.
  • Optimize data models for query performance, data integrity, and storage efficiency.
• Software Development and Integration:
  
  • Build software applications and APIs to expose data services and functionality to other systems and applications.
  • Integrate data engineering workflows with existing software systems and platforms.
• Monitoring and Maintenance:
  
  • Establish monitoring and alerting mechanisms to track the health and performance of data pipelines and systems.
  • Conduct regular maintenance activities to ensure the reliability, availability, and scalability of data infrastructure.
• Documentation and Collaboration:
  
  • Document data engineering processes, architectures, and solutions to facilitate knowledge sharing and collaboration.
  • Collaborate with cross-functional teams including data scientists, analysts, and business stakeholders to understand requirements and deliver solutions.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Proficiency in programming languages such as Python, Java, or Scala for data engineering and software development.
• Strong understanding of database concepts, data modeling techniques, and SQL programming.
• Hands-on experience with cloud platforms such as AWS, Azure, or GCP for building and deploying data solutions.
• Knowledge of data warehousing concepts and technologies (e.g., Redshift, BigQuery, Snowflake).
• Familiarity with version control systems (e.g., Git) and software development best practices (e.g., Agile, CI/CD).

Preferred Qualifications
 

• Experience building solutions for Commercial clients in Pharma, Biotech, CPG, Retail or Manufacturing industries.
• Experience with containerization technologies such as Docker and orchestration tools like Kubernetes.
• Knowledge of streaming data processing frameworks (e.g., Apache Flink, Apache Kafka Streams).
• Familiarity with data governance and security practices for protecting sensitive data.
• Strong problem-solving skills and the ability to troubleshoot complex data engineering issues.
• Excellent communication skills and the ability to collaborate effectively in a team environment.

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