Senior Data Engineer

Senior Data Engineer & Analytics Developer 61734 Target rate: $65/hr w2 Contract Length: 06-29-2026 to 12-08-2026 Location: Remote • • • Candidates must work on our W2 without needing sponsorship at any time now or in the future • • • We do not work with Corp to Corp in any manner including any form of referral bonus. These questions must be answered and will be included with your resume when submitting: 1. ??????How many Tableau dashboards have you built from scratch, not modified, but built end to end including the data layer behind them? And how did you build them? 1. How familiar are you with Cloud Composer? When would you use it over something simpler like a scheduled notebook or a cron job? 1. Have you ever had to combine data from multiple sources into a single dataset for reporting? Pick one example and tell me how you decided to structure it. 1. What is your Hands-on experience with SQL, Python, GCP, BigQuery, Cloud Composer, GCS, Cloud Functions, Jupyter notebooks — not just listed as keywords but demonstrated through pipeline builds, dataset design, or architecture decisions in prior roles. 1. What is your experience with scalable data architecture including reusable models, layered architectures (medallion, star schema), and consolidation? 1. What is your experience with Tableau dashboard development paired with data modeling — IE building both the data layer and the visualization on top of it? Role Summary Seeking a Data Engineer with strong analytics capability to own the full data lifecycle: scalable pipeline development through polished Tableau dashboards. Must think architecturally, design reusable datasets, avoid one-off tables, and be highly proficient in Python + SQL, with Tableau for reporting. Core Competencies — Data Engineering & Pipeline Development • Deep hands-on BigQuery: dataset design, partitioning/clustering, materialized views, cost optimization. • Cloud Composer / Airflow orchestration: scheduling, retries, dependency management for production pipelines. • Vertex AI Pipelines for ML workflows and large-scale transformations. • Advanced SQL: window functions, CTEs, recursive queries, optimization across large datasets. • Strong Python: transformation scripts, pipeline logic, custom Airflow operators, API integrations, automation. Data Architecture & Scalable Design • Design layered architectures: Medallion (bronze/silver/gold), star schema, Data Vault, targeted denormalization (apply per use case). • Build modular, multi-purpose datasets vs. project-specific tables; favor canonical models/shared dimensions. • Decide when to create new tables vs. extend/views/restructure existing assets to reduce duplication/table sprawl. • Best practices: naming conventions, schema organization, documentation, lifecycle management. Tableau Dashboard Development • Build production-quality dashboards: data source config, extract optimization, interactive design. • Translate business questions into intuitive self-serve visualizations. • Familiar with performance tuning, published data sources, and Tableau Server/Cloud publishing. • Designs upstream models with downstream dashboard performance in mind. Technical Stack • GCP, BigQuery (advanced), Cloud Composer/Airflow, Vertex AI Pipelines • Tableau (Desktop + Server/Cloud) • Python (advanced), SQL (advanced) • Terraform (preferred), GCS, Cloud Functions • Git/GitLab What Sets the Ideal Candidate Apart • Architecture-first: “Does this already exist? Can I extend it? Will it serve more than today’s ask?” • Efficiency over volume: fewer assets supporting more use cases. • End-to-end ownership from ingestion through dashboard. • Pragmatic scalability without over-engineering. Experience & Qualifications • 5+ years data engineering with meaningful GCP/BigQuery experience. • Advanced Python + SQL used daily. • Proven reusable enterprise data models (medallion/star schema/Data Vault). • Tableau portfolio/examples tied to well-structured data layers. • Familiar with CI/CD for pipelines and infrastructure-as-code concepts. • Strong communicator for requirements gathering and scalable solution design.