AI Data Engineer

AI Data Engineer

Overview

The Data Engineer, Advanced Analytics platforms will work with our core platform development team as well as domain experts, application developers, controls engineers and data scientists. Their primary responsibility will be to develop reliable and instrumented data ingestion pipelines that land inbound data from multiple process and operational data stores throughout the company to on-premises and cloud-based data lakes. These pipelines will require data validation and data profiling automation along with version control and CI/CD to ensure ongoing resiliency and maintainability of the inbound data flows supporting our advanced analytics projects.

Responsibilities

As a data engineer for our advanced analytics platforms, your main responsibilities will be:

• Design, test, deploy and maintain production big-data ingestion pipelines using established frameworks, patterns of practice, agile software development and CI/CD practices, working closely with the Principal Software Engineer – Data Ingestion
• Work with cross-organizational data source teams to define data ingestion requirements for structured, unstructured and semi-structured data, pilot their implementation, ensure the data source teams accept the resulting landed data as valid
• Define and implement automated validation and profiling capabilities needed to ensure reliable data delivery, using agile software development and CI/CD practices
• Work with data source teams, domain experts and data scientists to define data cleansing and data enrichment requirements for landed data
• Implement data cleansing and enrichment code using established patterns of practice General - Corning (L4)
• Work with data source teams, domain experts and data scientists to validate landed, cleansed and enriched data, using agile software development and CI/CD practices, while ensuring that the final datasets are directly usable by them without additional processing effort
• Actively participate in code reviews and technical information sharing with your team members and the broader software engineering community at Corning
• Stay up to date with industry standards and technological advancements that will improve the quality, productivity and performance of your work.
• Provide support in a DevOps environment to monitor tokens, jobs and overall system performance.

Qualifications

• Bachelor's degree in computer science, engineering, mathematics, or a related technical discipline
• Understand concepts of big data engineering, developing and maintaining ETL and ELT pipelines for data warehousing, on-premise and cloud data lake environments
• Demonstrated production programming proficiency in at least one modern JVM language such as Java, Scala or Kotlin, as well as an interpreted declarative programming language such as Python
• Entry level experience with AWS platform services, including AWS S3 & EC2, Data Migration Services (DMS), RDS, EMR, RedShift, Lambda, DynamoDB, CloudWatch, CloudTrail
• Hands-on technical familiarity with Apache Spark architecture, S3, parquet and Delta Lake architecture, technologies and tools
• Basic proficiency with both traditional relational and polyglot persistence technologies
• Familiarity with agile software development & continuous integration + continuous deployment methodologies along with supporting tools such as Git (Gitlab), Jira, Terraform, New Relic
• Familiarity with notebook environments including JupyterHub
• Able to Communicate well with users, other technical team to collect requirements, describe data modeling decisions.