Job description

Job Title: Senior Data Engineer Client & Practice Area: Data & AI Practice Experience Required: 7+ years of professional data engineering experience Employment Type: Full-time/Direct Hire (No C2C) Location: Hybrid in the DFW area; project will being as onsite T, W, Th in Fort Worth, TX (Candidates must be local) Please share your resume to venu.p@prudentconsulting.com Role Summary: Prudent Consulting is seeking a Senior Data Engineer to consolidate disparate data sources into a centralized, governed data warehouse and to build the GPU-accelerated data infrastructure needed to power downstream machine learning initiatives. This role will architect and operationalize pipelines on Dell AI Factory (Dell + NVIDIA) infrastructure, ensuring data is clean, reliable, and ML-ready. The ideal candidate combines deep data engineering expertise with hands-on experience deploying infrastructure on NVIDIA-accelerated compute environments. Key Responsibilities: • Design and build a centralized enterprise data warehouse, consolidating structured and unstructured data from multiple source systems. • Develop scalable ETL/ELT pipelines to ingest, clean, transform, and validate data at scale. • Architect and optimize data infrastructure on Dell AI Factory (Dell PowerEdge servers, NVIDIA GPUs, NVIDIA AI Enterprise software stack) for high-throughput processing. • Implement data governance, lineage, quality, and security controls aligned with enterprise and regulatory standards. • Partner with data scientists to prepare curated, ML-ready datasets and feature stores. • Optimize compute and storage utilization across on-prem/hybrid GPU-accelerated environments. • Translate business and technical requirements from TCU stakeholders into scalable data architecture. • Mentor junior engineers and establish reusable data engineering frameworks and standards. • Document data architecture, pipelines, and operational runbooks for long-term maintainability. Required Skills & Experience: • 7+ years of hands-on data engineering experience, including data warehouse/lakehouse design and large-scale pipeline development. • Strong proficiency in SQL and Python; experience with distributed data processing frameworks (e.g., Spark). • Experience with modern data stack tools such as Kafka, Airflow, or dbt. • Hands-on experience building and managing data warehouses/lakehouses (e.g., Snowflake, Databricks, Synapse, BigQuery, or on-prem equivalents). • Direct, hands-on experience with Dell AI Factory infrastructure and NVIDIA AI Enterprise GPU-accelerated computing — required. • Working knowledge of containerization and orchestration (Docker, Kubernetes) in on-prem/hybrid environments. • Solid understanding of data governance, security, and compliance frameworks. • Strong communication skills, with experience engaging directly with client stakeholders. Preferred / Added Value Skills: • Health sciences domain experience — clinical, healthcare, life sciences, or pharma data environments (e.g., HIPAA-regulated data handling, EHR/EMR data structures). • Experience with NVIDIA RAPIDS for GPU-accelerated data processing. • Experience with NVIDIA Triton Inference Server or NVIDIA NIM microservices. • Familiarity with MLOps pipelines and feature store design. • NVIDIA Deep Learning Institute (DLI) or Dell infrastructure/AI certifications. Education Requirements: • Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field (or equivalent practical experience).

Requirements

Must-haves

Job Title: Senior Data Engineer
Client & Practice Area: Data & AI Practice
Experience Required: 7+ years of professional data engineering experience
Employment Type: Full-time/Direct Hire (No C2C)
Location: Hybrid in the DFW area; project will being as onsite T, W, Th in Fort Worth, TX (Candidates must be local)
Please share your resume to venu.p@prudentconsulting.com
Design and build a centralized enterprise data warehouse, consolidating structured and unstructured data from multiple source systems.
Develop scalable ETL/ELT pipelines to ingest, clean, transform, and validate data at scale.
Architect and optimize data infrastructure on Dell AI Factory (Dell PowerEdge servers, NVIDIA GPUs, NVIDIA AI Enterprise software stack) for high-throughput processing.
Implement data governance, lineage, quality, and security controls aligned with enterprise and regulatory standards.
Partner with data scientists to prepare curated, ML-ready datasets and feature stores.
Optimize compute and storage utilization across on-prem/hybrid GPU-accelerated environments.
Translate business and technical requirements from TCU stakeholders into scalable data architecture.
Mentor junior engineers and establish reusable data engineering frameworks and standards.
Document data architecture, pipelines, and operational runbooks for long-term maintainability.
7+ years of hands-on data engineering experience, including data warehouse/lakehouse design and large-scale pipeline development.
Strong proficiency in SQL and Python; experience with distributed data processing frameworks (e.g., Spark).
Experience with modern data stack tools such as Kafka, Airflow, or dbt.
Hands-on experience building and managing data warehouses/lakehouses (e.g., Snowflake, Databricks, Synapse, BigQuery, or on-prem equivalents).
Direct, hands-on experience with Dell AI Factory infrastructure and NVIDIA AI Enterprise GPU-accelerated computing — required.
Working knowledge of containerization and orchestration (Docker, Kubernetes) in on-prem/hybrid environments.
Solid understanding of data governance, security, and compliance frameworks.
Strong communication skills, with experience engaging directly with client stakeholders.
Health sciences domain experience — clinical, healthcare, life sciences, or pharma data environments (e.g., HIPAA-regulated data handling, EHR/EMR data structures).

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningmlsqlpythondockerkubernetes

Platform: bullhorn
Effort: medium