Key skills
AWS Cloud servicesSQLPostgreSQLMySQLRedshiftAWS S3AWS LambdaAWS GlueAWS EMRAWS KinesisPythonJavaScalaData modelingETLData warehousingGitCI/CD pipelinesMachine learning frameworksData visualizationAmazon QuickSightQlikNoSQL databasesDynamoDBMongoDBNoSQLMachine LearningData EngineeringData WarehousingAnalyticsBusiness IntelligenceAWSLambdaS3GlueKinesisVersion ControlCI/CDProblem SolvingCollaboration
About this role
Emmes Group is a leading full-service contract research organization specializing in clinical research. The Data Engineer will design, build, and maintain scalable data pipelines and infrastructure to support data analytics and business intelligence initiatives, leveraging AWS Cloud services.
Responsibilities:
- Design, develop, and maintain robust data pipelines and ETL processes to ingest, transform, and store data from various sources
- Collaborate with data scientists, analysts, and other stakeholders to understand data requirements, design data models, and deliver solutions that meet business needs
- Automate data workflows and implement monitoring and logging to ensure the health and performance of the data infrastructure
- Conduct data profiling, cleansing, and validation to ensure high data quality standards
- Optimize data storage and retrieval performance, ensuring data quality and integrity
- Implement and manage data architecture on AWS, ensuring scalability, reliability, and security
- Stay up to date with the latest trends and best practices in data engineering and AWS cloud technologies
Requirements:
- Bachelor's or master's degree in computer science, Information Technology, or a related field
- 3 or more years of related professional experience
- Experience in data engineering strong focus on AWS cloud services
- Proficiency in SQL and experience with relational databases (e.g., PostgreSQL, MySQL, Redshift)
- Experience with AWS services such as S3, Lambda, Glue, EMR, Kinesis, and Redshift
- Strong programming skills in languages such as Python, Java, or Scala
- Knowledge of data modeling, ETL concepts, and data warehousing
- Familiarity with version control systems (e.g., Git) and CI/CD pipelines
- Excellent problem-solving skills and attention to detail
- Knowledge of machine learning frameworks and data science workflows
- Familiarity with data visualization tools (e.g., QuickSight, Qlik)
- Familiarity with NoSQL databases (e.g., DynamoDB, MongoDB)
- Strong collaboration skills with cross-functional teams to establish best design and user flows for applications
- Strong multitasking, problem solving, and organizational skills
- Proven ability to work independently and in a team environment
- Satisfactory background check required