Senior Data Engineer

Job Summary The primary responsibility of the Senior Data Engineer is designing, building, and maintaining the organization’s data platform infrastructure to support analytics, data science, AI, and application teams. This role ensures reliable, secure, and efficient data flow across enterprise systems while maintaining a scalable and governed data architecture. Responsibilities Designs, builds, and maintains scalable data pipelines and data architecture, including ELT/ETL processes across multiple data sources. Develops and publishes curated datasets and data products for analytics, reporting, machine learning, and application use cases. Administers and optimizes Snowflake environments, including database objects, warehouses, and role‑based access controls. Implements and enforces data governance practices such as data quality validation, metadata management, lineage tracking, and access policies. Collaborates with business and technical stakeholders to gather requirements, troubleshoot issues, and deliver data solutions. Monitors platform performance and resource utilization, implementing optimizations to balance cost and efficiency. Supports onboarding of new data sources and integration of enterprise systems into the data platform. Leads data incident response, root cause analysis, and remediation for pipeline or data quality issues. Maintains documentation for data architecture, pipelines, governance policies, and standards. Performs other duties as assigned. Qualifications Bachelor’s degree in Computer Science, Engineering, or related field. 6-8 years of experience in data engineering or related field. Strong experience designing and maintaining production‑grade data pipelines in cloud environments. Advanced proficiency in SQL and query optimization. Proficiency in Python for data processing and automation. Experience with Snowflake platform administration and performance tuning. Experience with data engineering tools such as Apache Spark, Airflow, dbt, or similar. Strong understanding of data modeling (dimensional modeling, schema design). Experience implementing data governance (RBAC, data quality, lineage, metadata). Familiarity with CI/CD practices and version control tools (Git). Strong analytical, problem‑solving, and troubleshooting skills. Excellent communication skills with ability to translate technical concepts to business stakeholders. Preferred Experience with Medallion architecture (Bronze/Silver/Gold layers). Experience supporting BI tools (Power BI, Tableau) and ML/AI pipelines. Experience integrating ERP, transactional, and third‑party data sources. Exposure to data mesh, data contract, or data product frameworks. Key Competencies Technical Depth – Advanced, hands‑on expertise across the full data engineering stack; approaches platform problems with rigor and translates that depth into reliable, production‑grade solutions. Platform Ownership – Takes end‑to‑end accountability for the health, performance, and evolution of the data platform; proactively identifies risks and drives resolution without waiting to be directed. Data Quality Mindset – Treats data as a product; consistently applies quality standards, governance practices, and documentation discipline to ensure platform consumers can trust what they receive. Stakeholder Partnership – Builds effective working relationships across technical and business teams; listens to understand needs, communicates transparently, and delivers solutions that address the underlying business problem. Problem Solving – Diagnoses complex pipeline failures, data anomalies, and performance issues methodically; brings structured thinking and creativity to both technical and process challenges. Adaptability – Thrives in dynamic, greenfield environments where priorities shift and patterns are still being established; comfortable with ambiguity and capable of making sound decisions with incomplete information. Collaboration – Works effectively across organizational boundaries; contributes generously to team knowledge sharing, documentation, and the success of adjacent teams. Continuous Improvement – Consistently looks for opportunities to improve platform reliability, engineering practices, and team effectiveness; stays current on relevant tools, frameworks, and industry patterns. Job duties outlined in this job description are considered “Essential Functions” and have been formulated in accordance with the guidelines established by the Equal Employment Opportunity Commission (EEOC). The provisions of the Americans with Disabilities Act (1990) stipulate that employees must be capable of performing the “Essential Functions” of the job with or without reasonable accommodation. Reasonable accommodations may be made to enable individuals with disabilities to perform the “Essential Functions”. DiversiTech is an Equal Opportunity Employer. #J-18808-Ljbffr