Key skills
Data EngineeringPythonDatabricksAWS ServicesBig DataData WranglingData AnalysisSoftware DevelopmentAgile EnvironmentLinuxCommunication SkillsTeam CollaborationGoMachine LearningBIRedshiftSparkKafkaData MiningAWSLambdaS3DynamoDBRDSGlueAgileCommunication
About this role
Abbott is a global healthcare leader that helps people live more fully at all stages of life. The Data Engineer role involves big data engineering, data wrangling, and data analysis in the Cloud, contributing to the implementation of Big Data Strategy and working with a team to solve business problems using data engineering and machine learning approaches.
Responsibilities:
- Design and implement data pipelines to be processed and visualized across a variety of projects and initiatives
- Develop and maintain optimal data pipeline architecture by designing and implementing data ingestion solutions on AWS using AWS native services
- Design and optimize data models on AWS Cloud using Databricks and AWS data stores such as Redshift, RDS, S3
- Integrate and assemble large, complex data sets that meet a broad range of business requirements
- Read, extract, transform, stage and load data to selected tools and frameworks as required and requested
- Customizing and managing integration tools, databases, warehouses, and analytical systems
- Process unstructured data into a form suitable for analysis and assist in analysis of the processed data
- Working directly with the technology and engineering teams to integrate data processing and business objectives
- Monitoring and optimizing data performance, uptime, and scale; Maintaining high standards of code quality and thoughtful design
- Create software architecture and design documentation for the supported solutions and overall best practices and patterns
- Support team with technical planning, design, and code reviews including peer code reviews
- Provide Architecture and Technical Knowledge training and support for the solution groups
- Develop good working relations with the other solution teams and groups, such as Engineering, Marketing, Product, Test, QA
- Stay current with emerging trends, making recommendations as needed to help the organization innovate
Requirements:
- Bachelors Degree in Computer Science, Information Technology or other relevant field
- At least 1-3 years of recent experience in Software Engineering, Data Engineering or Big Data
- Ability to work effectively within a team in a fast-paced changing environment
- Knowledge of or direct experience with Databricks and/or Spark
- Software development experience, ideally in Python, PySpark, Kafka or Go, and a willingness to learn new software development languages to meet goals and objectives
- Knowledge of strategies for processing large amounts of structured and unstructured data, including integrating data from multiple sources
- Knowledge of data cleaning, wrangling, visualization and reporting
- Ability to explore new alternatives or options to solve data mining issues, and utilize a combination of industry best practices, data innovations and experience
- Familiarity of databases, BI applications, data quality and performance tuning
- Excellent written, verbal and listening communication skills
- Comfortable working asynchronously with a distributed team
- Knowledge of or direct experience with the following AWS Services desired S3, RDS, Redshift, DynamoDB, EMR, Glue, and Lambda
- Experience working in an agile environment
- Practical Knowledge of Linux