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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data Engineer - **Company:** Infometry, Inc. - **Location:** Raleigh, NC, United States - **Experience:** Expert - **Salary:** $145,600.0 - $149,760.0 - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Data Analysis, Automation of Tests, Microsoft Azure, Cloud Computing, Code Review, Continuous Integration, Data as a Services, Data Architecture, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Mart, Data Masking, Data Vault Modeling, Data Warehousing, Relational Databases, Database Development, Dimensional Modeling, Python (Programming Language), Meta-Data Management, Metadata Repositories, Online Transaction Processing, Performance Tuning, Release Management, Cloud Services, Standard Sql, Simple Data Format, SQL Databases, Enterprise Data Management, Macros, Snowflake, Grafana, Change Data Capture, Git, Data Layers, Kubernetes, Information Technology, Data Management, Software Version Control, Data Pipelines - **Published:** July 29, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=063d015f7029cfdf ## About the Role Work Arrangement: Candidates must be able to work from one of the listed locations, * 9-10+ years of experience in data engineering, data warehousing, ETL/ELT, and enterprise data-platform delivery. * Strong hands-on experience with Snowflake architecture, SQL development, performance tuning, and administration concepts. * Advanced experience with dbt, including model development, macros, testing, documentation, packages, and deployment. * Proven experience implementing Data Vault 2.0 solutions using dbtvault or comparable frameworks. * Experience delivering an enterprise data warehouse using file-based data sources and multiple OLTP systems. * Strong experience with Snowpipe, stages, file formats, streams, tasks, and incremental ingestion patterns. * Strong understanding of Data Vault concepts, including hubs, links, satellites, hash keys, hash differences, effectivity, and historization. * Experience designing dimensional models, data marts, semantic layers, and analytical datasets. * Strong SQL, data-analysis, troubleshooting, and performance-optimization skills. * Experience with Git-based development, CI/CD pipelines, automated testing, and release management. * Ability to lead technical teams and communicate effectively with business and technology stakeholders. * Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline. Preferred Qualifications * Experience with AWS, Azure, or Google Cloud storage and data services. * Experience with Python, orchestration platforms, APIs, or event-driven data integration. * Familiarity with data catalogs, lineage, metadata management, governance, and observability tools. * Snowflake, dbt, or cloud-platform certifications. * Experience working in Agile delivery environments. What We Are Looking For The successful candidate will be a hands-on technical leader who can independently drive solution design while remaining actively involved in development and delivery. The candidate should have successfully implemented production-grade Snowflake data platforms and be comfortable managing complex data integration, modeling, quality, scalability, and performance requirements. Applicants must be U.S. Citizens or Green Card holders and must be available to work from Dallas, Raleigh, or Phoenix. ## Description We are seeking an experienced Lead Data Engineer with strong expertise in Snowflake, dbt, Snowpipe, and enterprise data warehouse development. The ideal candidate will have hands-on experience designing and delivering scalable cloud data platforms using dbt Vault/dbtvault, particularly for file-based data sources and multiple OLTP systems., This role requires a strong combination of data architecture, engineering leadership, dimensional and Data Vault modeling, performance optimization, and production delivery experience. The Lead Data Engineer will work closely with architects, business stakeholders, analysts, and engineering teams to build reliable, governed, and high-performing enterprise data solutions., * Lead the design, development, and implementation of enterprise data warehouse solutions on Snowflake. * Build scalable ingestion and transformation pipelines using Snowpipe, Snowflake, dbt, SQL, and related cloud technologies. * Design and implement Raw Vault, Business Vault, and information delivery layers using dbtvault. * Integrate data from file-based sources, APIs, relational databases, and multiple OLTP applications. * Develop reusable dbt models, macros, tests, documentation, and deployment standards. * Design incremental data-loading patterns, change data capture processes, historization, and audit frameworks. * Implement automated data-quality checks, reconciliation controls, exception handling, and monitoring. * Optimize Snowflake warehouses, queries, storage, clustering, and workload configurations for performance and cost. * Translate business and analytical requirements into scalable data models and technical solutions. * Establish engineering standards for naming conventions, source control, code reviews, testing, and CI/CD. * Provide technical leadership, conduct design reviews, mentor developers, and support delivery planning. * Troubleshoot production issues involving data pipelines, transformation logic, data quality, and performance. * Collaborate with security and governance teams to implement role-based access, data masking, lineage, and compliance controls. ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Crafting Custom Frameworks with Rust: A Deep Dive into Procedural Macros](https://www.wearedevelopers.com/videos/849-crafting-custom-frameworks-with-rust-a-deep-dive-into-procedural-macros) - [5 steps for running a Kubernetes environment at scale](https://www.wearedevelopers.com/videos/88-5-steps-for-running-a-kubernetes-environment-at-scale) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs)