rockITdata is looking to partner with leading commercial healthcare/life sciences organizations on cutting edge innovations like AI, automation and data transformation, and then bring those commercially tested solutions to government entities to deliver predictable, measurable impact for the American taxpayer and consumer. They are seeking a Full Stack Data Engineer to build end-to-end data solutions for diverse data projects and develop innovative data-driven applications.
Requirements
- 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).
- 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).
Responsibilities
- 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.
- Develop and maintain data storage solutions such as data lakes, data warehouses, and NoSQL databases.
- Implement data processing workflows for cleaning, transforming, and enriching raw data into usable formats.
- Design and implement data models to support analytical and reporting requirements.
- Build software applications and APIs to expose data services and functionality to other systems and applications.
- Establish monitoring and alerting mechanisms to track the health and performance of data pipelines and systems.
Other
- This is a Remote position.
- 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.
- Experience building solutions for Commercial clients in Pharma, Biotech, CPG, Retail or Manufacturing industries.
- Strong problem-solving skills and the ability to troubleshoot complex data engineering issues.
