{"schemaVersion":"jobsearcher.job.v1","id":"5f4cf9843b48698eee5797aa","url":"https://jobsearcher.com/jobs/5f4cf9843b48698eee5797aa","canonicalUrl":"https://jobsearcher.com/jobs/5f4cf9843b48698eee5797aa","title":"Sr Data Engineer & Analytics Developer","description":"Senior Data Engineer & Analytics DeveloperContract | GCP BigQuery Tableau PythonEmployment Type: ContractPay Rate: $65.00/hrStart Date: June 29, 2026End Date: December 8, 2026Role SummaryWe 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 thinks architecturally, designs datasets for reuse and longevity, and brings a builder’s mindset grounded in efficiency, modularity, and long-term sustainability of the data platform. Advanced proficiency in Python, SQL, and Tableau is required.Key ResponsibilitiesData Engineering & Pipeline DevelopmentDesign, build, and maintain production-grade data pipelines using Google BigQuery — including dataset design, partitioning/clustering strategies, materialized views, and cost optimization.Orchestrate complex pipelines using Cloud Composer (Apache Airflow) with proper scheduling, retry logic, and dependency management.Build and maintain Vertex AI Pipelines for ML workflows and large-scale data transformation.Write advanced, performant SQL across large datasets including window functions, CTEs, recursive queries, and query optimization.Develop Python scripts for data transformation, pipeline logic, custom Airflow operators, API integrations, and automation tooling.Data Architecture & Scalable DesignDesign layered data architectures using patterns such as Medallion (bronze/silver/gold), Dimensional Modeling (star schema), Data Vault, and targeted denormalization — applying the right pattern for each use case.Build modular, multi-purpose datasets rather than project-specific tables; think in terms of canonical models and shared dimensions.Determine when to create new tables versus extending, viewing, or restructuring existing assets to prevent unnecessary duplication and table sprawl.Apply best practices around naming conventions, schema organization, documentation, and lifecycle management.Tableau Dashboard DevelopmentBuild production-quality Tableau dashboards — from data source configuration and extract optimization to interactive visual design.Translate business questions into clear, intuitive visualizations that non-technical stakeholders can self-serve.Tune Tableau performance; manage published data sources and server/cloud publishing workflows.Design the data layer with downstream visualization performance in mind.Requirements5+ 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 able to work cross-functionally to gather requirements and deliver scalable data solutions.Preferred QualificationsExperience with Terraform for infrastructure-as-code.Familiarity with Google Cloud Storage (GCS) and Cloud Functions.Version control experience with Git/GitLab in a data engineering context.Technical StackCloud Platform: Google Cloud Platform (GCP)Data Warehouse: BigQuery (advanced)Orchestration: Cloud Composer / Apache AirflowML Pipelines: Vertex AI PipelinesVisualization: Tableau (Desktop, Server/Cloud)Languages: Python (advanced), SQL (advanced)Infrastructure: Terraform (preferred), GCS, Cloud FunctionsVersion Control: Git / GitLabWhat Sets The Ideal Candidate ApartArchitecture-first thinking — asks “Does this already exist? Can I extend what’s here? Will this serve more than just today’s ask?” before writing a single line of code.Efficiency over volume — measures success by how few tables and pipelines are needed to support a growing number of use cases, not how many are created.End-to-end ownership — comfortable moving from raw ingestion through to a polished Tableau dashboard, understanding how each layer impacts the next.Pragmatic scalability — designs for the future without over-engineering for the present; builds foundations that absorb new projects without architectural rework.","company":"Burtch Works","rawCompany":"burtch works","city":"Akron","state":"OH","isRemote":false,"isActive":false,"createdAt":"2026-06-17T01:52:33.215Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Sr Data Engineer & Analytics Developer","description":"Senior Data Engineer & Analytics DeveloperContract | GCP BigQuery Tableau PythonEmployment Type: ContractPay Rate: $65.00/hrStart Date: June 29, 2026End Date: December 8, 2026Role SummaryWe 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 thinks architecturally, designs datasets for reuse and longevity, and brings a builder’s mindset grounded in efficiency, modularity, and long-term sustainability of the data platform. Advanced proficiency in Python, SQL, and Tableau is required.Key ResponsibilitiesData Engineering & Pipeline DevelopmentDesign, build, and maintain production-grade data pipelines using Google BigQuery — including dataset design, partitioning/clustering strategies, materialized views, and cost optimization.Orchestrate complex pipelines using Cloud Composer (Apache Airflow) with proper scheduling, retry logic, and dependency management.Build and maintain Vertex AI Pipelines for ML workflows and large-scale data transformation.Write advanced, performant SQL across large datasets including window functions, CTEs, recursive queries, and query optimization.Develop Python scripts for data transformation, pipeline logic, custom Airflow operators, API integrations, and automation tooling.Data Architecture & Scalable DesignDesign layered data architectures using patterns such as Medallion (bronze/silver/gold), Dimensional Modeling (star schema), Data Vault, and targeted denormalization — applying the right pattern for each use case.Build modular, multi-purpose datasets rather than project-specific tables; think in terms of canonical models and shared dimensions.Determine when to create new tables versus extending, viewing, or restructuring existing assets to prevent unnecessary duplication and table sprawl.Apply best practices around naming conventions, schema organization, documentation, and lifecycle management.Tableau Dashboard DevelopmentBuild production-quality Tableau dashboards — from data source configuration and extract optimization to interactive visual design.Translate business questions into clear, intuitive visualizations that non-technical stakeholders can self-serve.Tune Tableau performance; manage published data sources and server/cloud publishing workflows.Design the data layer with downstream visualization performance in mind.Requirements5+ 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 able to work cross-functionally to gather requirements and deliver scalable data solutions.Preferred QualificationsExperience with Terraform for infrastructure-as-code.Familiarity with Google Cloud Storage (GCS) and Cloud Functions.Version control experience with Git/GitLab in a data engineering context.Technical StackCloud Platform: Google Cloud Platform (GCP)Data Warehouse: BigQuery (advanced)Orchestration: Cloud Composer / Apache AirflowML Pipelines: Vertex AI PipelinesVisualization: Tableau (Desktop, Server/Cloud)Languages: Python (advanced), SQL (advanced)Infrastructure: Terraform (preferred), GCS, Cloud FunctionsVersion Control: Git / GitLabWhat Sets The Ideal Candidate ApartArchitecture-first thinking — asks “Does this already exist? Can I extend what’s here? Will this serve more than just today’s ask?” before writing a single line of code.Efficiency over volume — measures success by how few tables and pipelines are needed to support a growing number of use cases, not how many are created.End-to-end ownership — comfortable moving from raw ingestion through to a polished Tableau dashboard, understanding how each layer impacts the next.Pragmatic scalability — designs for the future without over-engineering for the present; builds foundations that absorb new projects without architectural rework.","datePosted":"2026-06-17T01:52:33.215Z","dateModified":"2026-06-17T01:52:33.215Z","hiringOrganization":{"@type":"Organization","name":"Burtch Works","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Akron","addressRegion":"OH","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"5f4cf9843b48698eee5797aa"},"url":"https://jobsearcher.com/jobs/5f4cf9843b48698eee5797aa"}}