Note: The job is a remote job and is open to candidates in USA. InfoVision Inc. is seeking a Data Engineer specializing in Data & AI for Supply Chain solutions. The role involves designing and implementing scalable data pipelines on Google Cloud Platform, collaborating with various stakeholders, and optimizing data processing for enterprise applications.
Responsibilities
- Design, develop, and implement scalable data pipelines and data products on Google Cloud Platform (GCP)
- Build and optimize enterprise data solutions using Dataproc, BigQuery, SQL, and dbt
- Design robust and scalable data models that support analytical and operational reporting requirements
- Develop efficient ETL/ELT pipelines to ingest, transform, and publish data from multiple enterprise systems
- Collaborate with Product Managers, Business Analysts, Enterprise Solution Architects, Data Architects, and business stakeholders to translate business requirements into scalable technical solutions
- Lead technical design discussions and perform code reviews to ensure engineering quality and adherence to standards
- Optimize data processing performance, reliability, scalability, and cost across cloud-based data platforms
- Implement monitoring, testing, and operational best practices to support production workloads
- Contribute to reusable frameworks, engineering standards, and documentation that improve team productivity and solution consistency
- Support production issue resolution and continuous improvement initiatives
- Work effectively within Agile delivery teams and participate in sprint planning, estimation, and backlog refinement
- Mentor team members
Skills
- 5+ years of experience in Data Engineering with demonstrated technical leadership on enterprise data projects
- Strong hands-on experience with Google Cloud Platform (GCP)
- Expert-level proficiency in Dataproc
- Expert-level proficiency in BigQuery
- Expert-level proficiency in SQL
- Expert-level proficiency in dbt (Data Build Tool)
- Strong understanding of modern ETL/ELT architecture and large-scale data processing
- Strong knowledge of data modeling techniques, including dimensional modeling, normalized data models, and analytical data warehouse design
- Experience building scalable and maintainable cloud-native data pipelines
- Experience with Git, CI/CD pipelines, and engineering best practices
- Strong analytical, troubleshooting, and problem-solving skills
- Excellent verbal and written communication skills with the ability to collaborate effectively across cross-functional teams
- Experience with Apache Airflow for workflow orchestration
- Experience integrating enterprise data platforms with Apache Kafka or other streaming technologies
- Working knowledge of PySpark for distributed data processing
- Proficiency in Python for data engineering, automation, and utility development
- Familiarity with data quality, metadata management, and data governance best practices
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