Senior Data Engineer & Analytics

Nesco Resource is seeking a Data Engineer with strong analytics capabilities to own the full data lifecycle. The role involves developing scalable data pipelines, designing reusable datasets, and creating polished Tableau dashboards to support business needs.

Responsibilities:

• Build and maintain scalable data pipelines across Google Cloud Platform
• Design reusable datasets, shared dimensions, and canonical data models that support multiple business use cases
• Develop and optimize BigQuery datasets, including partitioning, clustering, materialized views, and cost optimization
• Orchestrate production-grade data pipelines using Cloud Composer and Apache Airflow
• Build and maintain Vertex AI Pipelines for ML workflows and large-scale data transformations
• Write complex, performant SQL using window functions, CTEs, recursive queries, and query optimization techniques
• Develop Python-based transformation scripts, pipeline logic, custom Airflow operators, API integrations, and automation tooling
• Build production-quality Tableau dashboards connected to well-structured data layers
• Translate business questions into clear, intuitive visualizations for non-technical stakeholders
• Apply data architecture best practices around naming conventions, schema organization, documentation, and lifecycle management

Requirements:

• 5+ years in a data engineering role, with meaningful GCP and BigQuery experience
• Advanced Python and SQL proficiency as daily working languages
• Hands-on experience with Google BigQuery, including dataset design and performance optimization
• Experience with Cloud Composer and Apache Airflow for pipeline orchestration
• Experience with GCS, Cloud Functions, and Jupyter notebooks
• Experience designing scalable, reusable data models in an enterprise or multi-team environment
• Familiarity with data architecture patterns such as Medallion, star schema, and Data Vault
• Hands-on Tableau dashboard development experience
• Understanding of how upstream data modeling decisions impact downstream dashboard performance
• Experience with Git or GitLab for version control
• Familiarity with CI/CD practices for data pipelines
• Experience with Vertex AI Pipelines
• Terraform experience
• Experience with infrastructure-as-code concepts
• Portfolio or examples of Tableau dashboards built on well-structured data layers
• Experience designing layered data architectures using bronze, silver, and gold patterns
• Experience with Tableau performance tuning, published data sources, and Server or Cloud publishing workflows