Senior Data Engineer, Architect

🔥 9 minutes ago

🤠 Texas – Remote

🤠 Texas – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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Presidio

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🤝 B2B

🤖 Artificial Intelligence

🔒 Cybersecurity

💰 Private equity on 2011-05

B2B • Artificial Intelligence • Cybersecurity

<Presidio> is a global technology services and solutions provider that designs, implements, and manages agile, secure digital platforms for enterprise customers. It helps organizations accelerate digital transformation through cloud migration and management, AI and data engineering, cybersecurity, networking and infrastructure, collaboration, and managed lifecycle services. Presidio also offers procurement, financing and consumption models, industry-specific solutions, and operational support for regulated and public sector clients.

📋 Description

• The Senior Data Engineer is a strong technical practitioner who builds, optimizes, and modernizes data pipelines, data platforms, and analytics infrastructure for enterprise clients. • You work across the full data engineering lifecycle—from ingestion and transformation to platform implementation and analytics enablement. • You understand the difference between code that works and code that holds up in production under real client conditions. • Contribute to solution design discussions alongside architects—bring engineering-level perspective on feasibility, complexity, and implementation trade-offs. • Help define data pipeline patterns, platform configurations, and engineering standards within the engagement.

🎯 Requirements

• Bachelor's Degree or equivalent experience and/or military experience • 5+ years in data engineering or cloud data platform development roles • 6+ years of advanced SQL knowledge across multiple database environments and data modeling patterns • Hands-on experience developing on modern cloud data platforms—Snowflake, Databricks, or equivalent; production-grade implementation experience, not just familiarity • Experience with cloud data stacks on AWS, Azure, and/or GCP (e.g., EMR, Redshift, Glue, Kinesis/Kafka, Azure Data Factory, Synapse, BigQuery, Dataproc) • Strong experience building data pipelines on Spark; proficiency in Python and/or Scala • Experience with data pipeline orchestration tools (Airflow, dbt, or similar) • Familiarity with lakehouse architectures, data mesh/fabric patterns, and modern data modeling approaches • Exposure to AI-ready data engineering—building pipelines and data foundations that support GenAI, Agentic AI, and ML workloads • Solid communication skills; ability to work with both technical teams and business stakeholders across client engagements.

🏖️ Benefits

• Health insurance • 401(k) matching • Flexible work hours • Paid time off • Professional development opportunities