Senior Data Engineer & Analytics Developer

Role Summary

We are seeking a Data Engineer with strong analytics capabilities who can own the full data lifecycle — from scalable pipeline development to polished Tableau dashboards. The ideal candidate is someone who thinks architecturally, designs datasets for reuse and longevity, and resists the urge to create one-off tables for every new request. They bring a builder's mindset grounded in efficiency, modularity, and long-term sustainability of the data platform.

They must be highly proficient in both Python and SQL as their primary working languages and Tableau for reporting.

• Deep, hands‑on experience with Google Big Query — including dataset design, partitioning/clustering strategies, materialized views, and cost‑optimization techniques.
• Proficiency in Cloud Composer (Apache Airflow) for orchestrating complex, production‑grade data pipelines with proper scheduling, retry logic, and dependency management.
• Experience building and maintaining Vertex AI Pipelines for ML workflows and data transformation at scale.
• Advanced SQL skills — able to write complex, performant, and maintainable queries across large datasets including window functions, CTEs, recursive queries, and query optimization.
• Strong Python proficiency — comfortable building data transformation scripts, pipeline logic, custom Airflow operators, API integrations, and automation tooling.

• Proven ability to design layered data architectures using patterns such as Medallion (bronze/silver/gold), Dimensional Modeling (star schema), Data Vault, and targeted denormalization — and knows when to apply each based on the use case.
• Track record of building modular, multi‑purpose datasets rather than project‑specific tables — thinks in terms of canonical models and shared dimensions.
• Understands when to create new tables versus when to extend, view, or restructure existing assets to avoid unnecessary duplication and table sprawl.
• Applies best practices around naming conventions, schema organization, documentation, and lifecycle management so that the architecture remains navigable as it scales.

• Hands‑on experience building production‑quality Tableau dashboards — from data source configuration and extract optimization to interactive visual design.
• Ability to translate business questions into clear, intuitive visualizations that non‑technical stakeholders can self‑serve from.
• Familiarity with Tableau performance tuning, published data sources, and server/cloud publishing workflows.
• Understands the relationship between upstream data modeling decisions and downstream dashboard performance — designs the data layer with the visualization in mind.

• Cloud Platform:
  Google Cloud Platform (GCP)
• Data Warehouse:
  Big Query (advanced)
• Orchestration:
  Cloud Composer / Apache Airflow
• ML Pipelines:
  Vertex AI Pipelines
• Visualization:
  Tableau (Desktop, Server/Cloud)
• Languages:
  
  Python (advanced), SQL (advanced)
• Infrastructure:
  Terraform (preferred), GCS, Cloud Functions
• Version Control:
  Git / Git Lab

Everforth Apex Systems is an equal opportunity employer. We do not discriminate or allow discrimination on the basis of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), age, sexual orientation, gender identity, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, disability, status as a crime victim, protected veteran status, political affiliation, union membership, or any other characteristic protected by law.

Everforth Apex will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable law.