GCP Data Engineer

Data Engineer

Location: Hybrid (3x onsite) 2 location options: Houston TX (Downtown) Evansville IN 47708

Project Details: Looking for a Data Engineer that will work in the IT and Data Analytics group at. They will help with developing, constructing, testing and maintaining data acquisition pipelines for large volumes of data. This includes batch and real time processing. They will build help with building large datasets, and collaborate with stakeholders to identify opportunities for data acquisition. Looking for someone who can facilitate the overarching data process from python all the way through to SQL.

Must Have Skills:

• Level 2: Bachelor's degree in Data Science, Analytics, Mathematics, Statistics, Computer Science or STEM
• Minimum of 2 years' experience of related experience in data engineering, data analysis, ETL or similar role delivering data pipelines
• Experience with Python and Strong Proficiency in SQL with direct working experience leveraging this skill
• Understanding in data modeling concepts and experience with data modeling tools

Level 3:

• Minimum of 5 years' experience of related experience in data engineering, data analysis, ETL or similar role delivering data pipelines
• Experience with Google Big Query, Python and Strong Proficiency in SQL with direct working experience leveraging this skill
• Understanding in data modeling concepts and experience with data modeling tools
• GCP experience

Nice to have Skills:

• Utility experience
• Experience with data governance
• Experience working in an agile team environment

Day to Day Responsibilities:

• Develop, construct, test and maintain data acquisition pipelines for large volumes of structured and unstructured data. This includes batch and real-time processing.
• Build large and complex datasets based on business requirements.
• Construct 'big data' pipeline architecture
• Identifies opportunities for data acquisition via collaborating with stakeholders and business clients.
• Leverages a variety of tools such as Python, SAP Data Services, Dataflow, DataStream, Google Cloud Functions, Spark, Google Cloud Run, SAP SLT, Google Pub Sub, etc. to integrate systems and data pipelines.
• Recommends ways to improve data quality, reliability, and efficiency.
• Develop JSON messaging structure for integrating with various applications.