Data Engineer

Data EngineerLocation: Springfield, MO / Dallas, TX / Austin, TX / Atlanta, GAAbout LatentViewLatentView Analytics is a global data analytics and AI solutions company that partners with Fortune 500 and high-growth clients to turn data into competitive advantage. Our teams combine deep technical expertise with business context to ship measurable outcomes — not just models and dashboards — across industries.Role OverviewThe Lead Data Engineer will be responsible for the end-to-end architecture, development, and scaling of the enterprise cloud data platform. This role bridges the gap between complex business requirements and robust, scalable technical implementations. The primary objective is to design, build, and optimize modern ELT data pipelines, establishing a highly performant and reliable data foundation using Snowflake and dbt (Data Build Tool).This position requires the application of advanced data modeling concepts, distributed computing principles, and strict software engineering best practices. Furthermore, the Lead Data Engineer will act as a key technical advocate, requiring strong stakeholder management skills and the ability to confidently present technical strategies, data models, and infrastructure designs to the Enterprise Architecture Board for review and approval.Key Duties and Responsibilities1. Data Architecture & Pipeline Engineering (40%)Architect, build, and maintain scalable ELT pipelines loading data from various sources into Snowflake.Design and develop modular, reusable, and efficient data models using dbt to transform raw data into analytics-ready "Certified Data Sets."Optimize Snowflake performance, managing virtual warehouses, clustering, and storage to balance high-performance querying with cost efficiency.Implement advanced data modeling techniques (e.g., Dimensional Modeling, Data Vault) to support changing enterprise requirements.2. Technical Stakeholder Management & Architecture Governance (30%)Lead technical discussions and manage expectations with senior stakeholders across Product, Finance, Analytics, and Data Science teams to translate business needs into technical architecture.Prepare and present technical blueprints, system architectures, and tool-selection rationales to the Enterprise Architecture Board for feedback and approval.Act as a technical steward, negotiating technical trade-offs with stakeholders to prevent technical debt while delivering on strategic business initiatives.Mentor junior and mid-level data engineers, driving a culture of engineering excellence and architectural standard adherence.3. Data Quality, Orchestration & CI/CD Validation (20%)Design and integrate automated data quality testing within the dbt workflow (using generic and singular tests, or packages like dbt-expectations) to ensure data completeness, accuracy, and consistency.Orchestrate complex data workflows using modern orchestration tools (e.g., Apache Airflow, Dagster, or Prefect).Implement and maintain CI/CD pipelines (e.g., GitHub Actions, GitLab CI) for seamless, version-controlled deployment of Snowflake infrastructure and dbt transformations.Perform root-cause analysis on pipeline failures or data discrepancies, resolving issues between source systems and the data warehouse.4. Strategic Documentation & Compliance (10%)Create and maintain detailed technical documentation, including Data Flow Diagrams (DFDs), entity-relationship models, and architecture decision records (ADRs).Implement data security best practices within Snowflake, including Role-Based Access Control (RBAC), row-level security, and dynamic data masking to ensure compliance with GDPR/CCPA and protect Personally Identifiable Information (PII).Minimum RequirementsEducation: Bachelor’s Degree (Master’s preferred) in Computer Science, Information Systems, Software Engineering, Mathematics, or a closely related quantitative field.Experience: Minimum of 5-7 years of progressive experience in Data Engineering, Data Architecture, or Software Engineering, with a proven track record of leading complex data projects.Specialized Skills & ToolsTo perform the complex duties listed above, the candidate must possess the following specialized technical skills:Cloud Data Warehousing: Deep expertise in Snowflake (architecture, performance tuning, query optimization, and cost management).Data Transformation: Advanced proficiency in dbt (Data Build Tool), including macros, incremental models, and Jinja templating.Programming & Querying: Expert-level proficiency in SQL for complex data manipulation, and strong programming skills in Python for custom scripting, API integrations, and orchestration.Architecture & Presentation: Demonstrated experience presenting technical designs to Architecture Review Boards, and strong verbal/written communication skills for technical stakeholder management.Data Modeling: Comprehensive understanding of Star Schema, Snowflake Schema, and modern cloud-native data modeling concepts.DevOps & Orchestration: Hands-on experience with Git, CI/CD workflows, and workflow orchestration tools (Airflow, Prefect, etc.).Required skills :Advanced SQL, Primary Skills Cloud Data Warehousing (Snowflake): Deep expertise in Snowflake architecture, virtual warehouse management, performance tuning, query optimization, and cost management. Data Transformation (dbt): Advanced proficiency in Data Build Tool (dbt), including building modular models, incremental materialization, macros, and Jinja templating. Querying & Programming: Expert-level SQL for complex data manipulation and strong Python skills for data extraction, API integration, and custom scripting. Data Architecture & Modeling: Hands-on experience designing scalable ELT pipelines and applying modern data modeling techniques (Dimensional Modeling, Star/Snowflake Schema, Data Vault). Stakeholder Management & Technical Leadership: Proven ability to translate business requirements into technical blueprints, negotiate trade-offs, and confidently present designs to Enterprise Architecture Boards.Base pay range: USD $137,700 – USD $ 160,200 annually. This range reflects base salary only — it excludes Incentive and benefits — and is a good-faith estimate for this level and location that may vary based on experience, skills, and where the role is performed.Communication: This role requires fluent spoken and written English to communicate directly with client stakeholders — a job-related requirement of the client-facing work itself, not of any candidate's background or origin.