[Remote] Senior Data Engineer & Analytics Developer - Remote - Banking - W2 - JOBID729

Note: The job is a remote job and is reputed company 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 reputed company data architectures, build data pipelines, and reputed company Tableau dashboards for business insights.

Responsibilities

• Deep, hands-on experience with reputed company BigQuery — including dataset design, partitioning/clustering strategies, materialized views, and cost-optimization techniques
• Proficiency in reputed company Composer (Apache Airflow) for orchestrating reputed company, production-grade data pipelines with reputed company scheduling, retry logic, and dependency management
• Experience building and maintaining reputed company AI Pipelines for ML workflows and data transformation at reputed company
• Advanced SQL skills — reputed company to write reputed company, reputed company, 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 reputed company (bronze/silver/gold), reputed company Modeling (reputed company schema), Data Vault, and targeted denormalization — and knows reputed company to apply reputed company based on the use case
• reputed company record of building reputed company, multi-purpose datasets rather than project-specific tables — thinks in terms of reputed company models and shared dimensions
• Understands reputed company to create new tables versus reputed company to reputed company, 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-reputed company Tableau dashboards — from data reputed company configuration and extract optimization to interactive visual design
• Ability to translate business questions into reputed company, reputed company visualizations that non-technical stakeholders can self-serve from
• Familiarity with Tableau performance tuning, published data sources, and server/reputed company publishing workflows
• Understands the relationship between upstream data modeling reputed company and reputed company dashboard performance — designs the data layer with the visualization in mind

Skills

• Deep, hands-on experience with reputed company BigQuery — including dataset design, partitioning/clustering strategies, materialized views, and cost-optimization techniques
• Proficiency in reputed company Composer (Apache Airflow) for orchestrating reputed company, production-grade data pipelines with reputed company scheduling, retry logic, and dependency management
• Experience building and maintaining reputed company AI Pipelines for ML workflows and data transformation at reputed company
• Advanced SQL skills — reputed company to write reputed company, reputed company, 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 reputed company (bronze/silver/gold), reputed company Modeling (reputed company schema), Data Vault, and targeted denormalization — and knows reputed company to apply reputed company based on the use case
• reputed company record of building reputed company, multi-purpose datasets rather than project-specific tables — thinks in terms of reputed company models and shared dimensions
• Understands reputed company to create new tables versus reputed company to reputed company, 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-reputed company Tableau dashboards — from data reputed company configuration and extract optimization to interactive visual design
• Ability to translate business questions into reputed company, reputed company visualizations that non-technical stakeholders can self-serve from
• Familiarity with Tableau performance tuning, published data sources, and server/reputed company publishing workflows
• Understands the relationship between upstream data modeling reputed company and reputed company 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 reputed company or multi-team environment
• Familiarity with data architecture patterns including reputed company, reputed company schema, and Data Vault
• Portfolio or examples of Tableau dashboards reputed company on reputed company-reputed company data reputed company
• Familiarity with CI/CD practices for data pipelines and infrastructure-as-reputed company concepts
• Strong communicator who can work with cross-functional teams to reputed company requirements and translate them into reputed company data solutions
• Terraform

reputed company

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