Note: The job is a remote job and is open to candidates in USA. Outcome Logix is a Tech 50 Finalist company recognized by the Pittsburgh Technology Council. They are seeking a Senior Data Engineer & Analytics Developer to design and implement scalable data architectures, build data pipelines, and develop Tableau dashboards for business insights.

Responsibilities

• Deep, hands-on experience with Google BigQuery — 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

Skills

• Deep, hands-on experience with Google BigQuery — 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
• 5+ years in a data engineering role, with meaningful GCP/BigQuery experience
• Advanced proficiency in Python and SQL as daily working languages
• Demonstrated experience designing and maintaining shared, reusable data models in an enterprise or multi-team environment
• Familiarity with data architecture patterns including Medallion, star schema, and Data Vault
• Portfolio or examples of Tableau dashboards built on well-structured data layers
• Familiarity with CI/CD practices for data pipelines and infrastructure-as-code concepts
• Strong communicator who can work with cross-functional teams to gather requirements and translate them into scalable data solutions
• Terraform

Company Overview

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