Data Engineer

Job Summary The Data Engineer will design, build, and optimize scalable data solutions across cloud (GCP) and on-prem environments. This role focuses on re-platforming data services, enabling real-time streaming, and ensuring data quality, performance, and reliability. You’ll help shape our enterprise data and analytics platform to support modern analytics lifecycles—enabling data monetization, feature engineering, model training, reporting, and predictive insights. Key Responsibilities • Design and implement cloud-native data pipelines and architectures using Google Cloud Platform (BigQuery, Pub/Sub, Dataflow, Dataform, BigTable, Cloud Composer, Cloud Run, IAM, Terraform). • Develop and optimize ETL processes, data curation, and modeling using Python and SQL. • Lead data solution design sessions, code reviews, and CI/CD pipeline automation (Azure DevOps, Terraform/Terragrunt). • Collaborate with architecture and analytics teams to define scalable, secure data foundations and frameworks for both certified and self-service analytics. • Improve system efficiency, data quality, and SLA management for high-performance data processing and ML model support. • Ensure strong governance, monitoring, and data security practices (Secret Manager, IAM, Logging, Monitoring). Qualifications • Bachelor’s degree in Computer Science, Engineering, or related field. • 5+ years in data engineering, modeling, and architecture; 3+ years in data analytics solution design. • Proven expertise in GCP data tools, Python, SQL, and distributed frameworks like Spark. • Strong understanding of data modeling, data governance, and cloud data infrastructure. • Experience with Agile/Scrum delivery, CI/CD, and DevOps best practices. Preferred • GCP Professional Data Engineer Certification. • Experience in the Energy Sector. • Strong documentation and communication skills to translate technical concepts for business stakeholders.