Home-Based DCX Data Engineer

It's fun to work in a company where people truly BELIEVE in what they're doing! We're committed to bringing passion and customer focus to the business. Active Hiring Opportunity Number of Openings: 1 The Home-Based DCX Data Engineer plays a foundational role in building and maintaining the data infrastructure that powers analytics, reporting, and AI-driven capabilities for the business. This position is responsible for designing and operationalizing data pipelines, managing data transformation workflows, and ensuring that high-quality, reliable data is available to internal consumers across the organization. This role reports to the Vice President of Technology and works directly with Snowflake as the core data platform, collaborating closely with technology leadership and cross-functional stakeholders to translate data requirements into scalable, well-governed solutions. REQUIRED CORE COMPETENCIES - Analytical Thinking: Strong analytical mindset with close attention to data quality and accuracy across pipelines and models. - Communication: Effective communicator, able to translate complex data concepts into clear, actionable language for both technical teammates and non-technical business stakeholders. - Adaptability: Curious and proactive, with a genuine interest in learning new tools, platform features, and engineering practices as needs evolve. - Engineering Judgment: Sound decision-making in evaluating tradeoffs across ingestion patterns, storage strategies, and transformation approaches. - Collaboration: Able to function well in a cross-functional, fast-evolving environment, partnering effectively across engineering, analytics, and leadership teams. WHAT YOU WILL DO - Design, build, and maintain scalable ETL/ELT pipelines that move data reliably from source systems into Snowflake for downstream consumption - Implement pipeline orchestration with proper scheduling, monitoring, alerting, and recovery on failure or data quality degradation - Develop and manage Snowflake objects (databases, schemas, tables, views, stages, streams, tasks, stored procedures) to support ingestion, transformation, and access patterns - Optimize query performance and warehouse utilization through clustering, partitioning, and warehouse sizing strategies - Implement and enforce Snowflake role-based access control (RBAC) policies across environments - Design and implement dimensional/relational data models with a clear layering strategy across raw, conformed, and consumption zones - Leverage dbt or equivalent tooling to build modular, version-controlled, tested SQL transformations - Implement data quality checks, anomaly detection, and lineage tracking - Apply data classification, masking policies, and retention rules to protect sensitive information and support compliance - Contribute to a data catalog and metadata management practices - Partner with business analysts, data scientists, and application developers to deliver well-structured datasets - Maintain thorough documentation of pipeline architecture, data models, transformation logic, and platform configurations - Ad hoc tasks aligned with those mentioned above WHAT WE LOOK FOR - Education: Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field - Experience: 2+ years of professional experience in a data engineering role, with direct, hands-on experience building pipelines and data models in Snowflake. - Language Proficiency: Very proficient written and spoken English - Working schedule: 8:00 AM – 5:00 PM CST, Monday through Friday - Technical Skills: Strong proficiency in SQL; working knowledge of Python or a comparable scripting language - Industry-Specific Software/Knowledge: - Deep technical expertise in Snowflake, including architecture, performance optimization, security configuration, and native features (Snowpark, Cortex, dynamic tables) - Familiarity with dimensional m