Data Engineer

GCP Data Engineer in Houston, TX or Evansville, IN

Top Skills:

Requires a minimum of five (5) years of related experience in data engineering, data analysis, ETL or similar role delivering data pipelines.

Experience with Google Big Query.

Strong proficiency in SQL with direct working experience leveraging this skill.

Experience with data exploration tools like KNIME/Alteryx

Understanding of data modeling concepts and experience with data modeling tools.

Proficiency in ETL processes, data warehousing, and database management systems.

Experience working with the following tools: Dataflow, DataStream, Google Cloud Functions, Spark, Google Cloud Run, Google Pub Sub , etc. to integrate systems and data pipelines.

Roles and Responsibilities:

Develop, construct, test and maintain data acquisition pipelines for large volumes of structed 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.

Drive a data engineering strategy focused on delivering data in near real-time using server less technologies.

Develop data architecture to optimize performance for dashboards and digital applications.

Lead the integration track of various strategic projects.

Leverage DevOps and CI/CD practices to ensure the reliability and scalability of data pipelines.

Assist in the development and maintenance of data models, data dictionaries, and data documentation to ensure data integrity and consistency.

Participate in cross-functional teams to support data-related projects, providing expertise and guidance on data analysis, data management, and data visualization.

Stay updated with the latest industry trends and advancements in data analytics, data science, and data engineering, and apply this knowledge to enhance data capabilities within the organization.

Constant, initiative-taking pursuit of learning systems, organizational structure, processes, data sets, techniques, etc.

Interpret and explain information to audiences who are not familiar with the subject matter, often requiring persuasion.

Provide guidance and training to others in the use of modern technologies, theories, concepts, and techniques.

Operate with limited supervision, guidance, and direction from leadership and senior staff