Data Engineer

Our Dallas based client is seeking a Senior Data Engineer, to be a key technical leader responsible for designing, building, and owning scalable, reliable, and well-governed data solutions that enable enterprise analytics and decision-making. This role operates at the intersection of data engineering, analytics enablement, and governance. The Senior Data Engineer will own complex data pipelines and curated data products, and will partner closely with analytics and business stakeholders, and set technical standards that improve data quality, usability, and trust across the organization. The Senior Data Engineer will be comfortable operating with ambiguity, will be able to independently own data domains end-to-end, and will serve as a mentor and force multiplier within the data engineering team., 1. Data Engineering & Platform Ownership

• Design, build, and own end-to-end ETL/ELT pipelines across diverse data sources using Palantir Foundry, PySpark, pandas, and SQL
• Architect scalable, resilient data integration solutions supporting analytics, reporting, and operational use cases
• Own ingestion, transformation, validation, and monitoring workflows to ensure data accuracy, availability, and performance
• Manage and optimize data lake and warehouse environments within a cloud-based SaaS ecosystem
• Establish and maintain integrations with enterprise systems and external platforms (e.g., ERP, CRM, advertising platforms)
• Troubleshoot complex data issues, perform root-cause analysis, and implement long-term fixes

2. Analytics Enablement and Data Applications

• Develop analytics-ready datasets and curated data products that enable self-service reporting and analysis
• Build and maintain custom analytics applications using Palantir Foundry Workshop and backend tools (Pipeline Builder, PySpark, pandas)
• Partner with business analysts, analytics consumers, and department leaders to translate commercial and operational questions into scalable data solutions
• Automate reporting and dashboarding workflows to reduce manual effort and improve data accessibility
• Enable advanced analytical use cases by delivering feature-ready datasets (e.g., for forecasting, trend analysis, or anomaly direction), without owning full data science model lifecycle unless explicitly required

3. Data Governance, Standards, and Security

• Support and enhance data governance frameworks that improve data quality, consistency, security, and compliance
• Collaborate with stakeholders to define and enforce data standards, naming conventions, and access policies
• Enhance and maintain role-based access controls (RBAC) in partnership with IT and security teams
• Contribute to medallion architecture design, data modeling standards, and metadata and/or documentation practices

4. Technical Leadership and Mentorship

• Serve as a senior technical resource for the team, providing design guidance, code reviews, and architectural input
• Mentor junior and mid-level engineers through structure feedback, documentation standards, and modeling best practices
• Set and reinforce expectations for maintainability, reliability, and clarity in data engineering work
• Participate in design reviews and help establish long-term technical direction for the data platform

5. Documentation and Continuous Improvement

• Build and maintain clear, comprehensive technical documentation for pipelines, data products, and integrations
• Identify opportunities to improve tooling, methodologies, and development workflows
• Stay current on data engineering and analytics best practices and selectively introduce improvements that add real value

6. All other duties as assigned

Skills: Data Engineer, Python, SQL, ETL, Palantir Foundry, Pyspark, Pandas, * Bachelor's degree in information technology, computer science, or a related field (or equivalent experience)

• 5+ years of progressive experience in data analytics, analytics engineering, or business intelligence roles
• Must have intermediate experience with Microsoft Office products to include Word, Excel, PowerPoint, and Outlook
• Must have strong hands-on experience with Palantir Foundry, including Pipeline Builder and Workshop
• Must have advanced proficiency in PySpark and SQL for large-scale data transformation
• Must have strong Python skills (pandas, familiarity with polars is a plus)
• Must have a solid understanding of data modeling and medallion architecture
• Must have experience integrating data from ERP, CRM, POS, or similar enterprise systems
• Must have experience implementing or supporting data governance and access control models
• Must have proficiency with Git-based version control and collaborative development workflows
• Must have the ability to operate independently, manage ambiguity, and own outcomes
• Detail oriented with excellent time management and follow up skills
• Must have strong communication skills with experience engaging both technical peers and business stakeholders
• Experience integrating with Meta Ads, Google Ads, or other marketing platforms preferred
• Palantir certifications preferred
• Industry experience in maritime, real estate, hospitality, or asset-heavy, multi-unit operating environments preferred
• Experience supporting analytics in finance, operations, or revenue management contexts preferred