Staff Data Engineer

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Responsible for managing business critical data engineering processes and data architecture solutions in order to enable analytical and reporting solutions. Responsible for analyzing and preparing the data needed for data science based outcomes. Also responsible for managing and maintaining metadata data structures besides providing necessary support for post-deployment related activities. Accountable to deliver results in a timely manner using agile methodologies.

GE Healthcare is a leading global medical technology and digital solutions innovator. Our mission is to improve lives in the moments that matter. Unlock your ambition, turn ideas into world-changing realities, and join an organization where every voice makes a difference, and every difference builds a healthier world.

Job Description

Roles and Responsibilities

• Design & build technical data dictionaries and support business glossaries to analyze the datasets
• Perform data profiling and data analysis for source systems, manually maintained data, machine or sensor generated data and target data repositories
• Design & build both logical and physical data models for both Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) solutions
• Develop and maintain data mapping specifications based on the results of data analysis and functional requirements
• Build a variety of data loading & data transformation methods using multiple tools and technologies.
• Design & build automated Extract, Transform & Load (ETL) jobs based on data mapping specifications
• Manage metadata structures needed for building reusable Extract, Transform & Load (ETL) components.
• Analyze reference datasets and familiarize with Master Data Management (MDM) tools.
• Analyze the impact of changes to downstream systems/products and recommend alternatives to minimize the impact.
• Derive solutions and make recommendations from deep dive data analysis proactively.
• Design and build Data Quality (DQ) rules.

Qualification

• Bachelor's Degree in Computer Science or STEM” Majors (Science, Technology, Engineering and Math) with advanced experience.

Desired Characteristics

• Exposure to industry standard data modeling tools (e.g., ERWin, ER Studio, etc.).
• Exposure to Extract, Transform & Load (ETL) tools like Informatica or Talend
• Exposure to industry standard data catalog, automated data discovery and data lineage tools (e.g., Alation, Collibra, etc., )
• Hands-on experience in programming languages like Java, Python or Scala
• Hands-on experience in writing SQL scripts for Oracle, MySQL, PostgreSQL or HiveQL
• Experience with Big Data / Hadoop / Spark / Hive / NoSQL database engines (i.e. Cassandra or HBase)
• Exposure to unstructured datasets and ability to handle XML, JSON file formats
• Conduct exploratory data analysis and generate visual summaries of data. Identify data quality issues proactively.

Domain Expertise

• Exposure to handling machine or sensor datasets from industrial businesses
• Knowledge of for industrial applications in a commercial/finance/industrial/manufacturing settings.
• Exposure to finance and accounting data domains