Senior Data Engineer

The Senior Data Analyst / Engineer will architect and maintain scalable data pipelines, design performant relational models, and deliver high-impact analytical insights that influence business direction. This role blends hands-on engineering with advanced analytics and requires the ability to translate ambiguous business problems into structured, data-driven solutions. Operating with autonomy, this individual will shape data architecture decisions, implement governance and quality controls, and continuously improve how information is structured and consumed across the organization. Over time, this role will help define the long-term direction of the data function and support the development of a high-performing data capability.

Hybrid - Based in Mobile, AL (other offices may be available) 

• Architect, build, and maintain scalable ETL/ELT pipelines that support operational and analytical workloads
• Design and optimize relational data models for performance, integrity, and long-term maintainability
• Own SQL performance tuning, indexing strategies, and execution plan analysis across large datasets
• Establish data validation, monitoring, and quality controls to ensure reliability and traceability
• Translate ambiguous business problems into structured analytical frameworks and deliver executive-ready insights that inform strategic decisions
• Automate manual reporting processes and improve efficiency through durable technical solutions
• Define and enforce standards for data structure, naming conventions, documentation, and governance
• Identify systemic weaknesses in current data processes and implement corrective architectural improvements
• Collaborate with engineering and DevOps to ensure cloud-based data infrastructure is secure, scalable, and resilient
• Mentor analysts and elevate technical standards across the data function
• Contribute to roadmap discussions by providing data-informed perspective and forward-looking insight

• Operate with a high degree of autonomy and take ownership of outcomes, not just assigned tasks
• Anticipate data needs and structural challenges before they become operational constraints
• Design solutions that are durable, scalable, and aligned with long-term organizational growth
• Elevate standards for data quality, modeling, documentation, and reproducibility
• Move beyond reactive reporting to proactive insight generation
• Demonstrate sound architectural judgment when balancing performance, complexity, and maintainability
• Communicate analytical findings clearly and concisely to both technical and executive audiences
• Influence decision-making through rigorous analysis and thoughtful interpretation
• Hold yourself accountable for measurable impact and continuous improvement
• Contribute to strengthening the overall data capability of the organization through mentorship and example

• Advanced SQL expertise, including window functions, CTEs, performance tuning, and execution plan analysis
• Strong understanding of relational database design, normalization principles, and data modeling techniques
• Experience designing, building, and maintaining production-grade ETL/ELT pipelines
• Proficiency in working with cloud-based data environments and services
• Deep understanding of data integrity, validation strategies, and quality control frameworks
• Ability to structure ambiguous business problems into measurable analytical approaches
• Strong analytical reasoning and quantitative problem-solving skills
• Experience automating data workflows and reducing manual operational dependencies
• Ability to design systems with scalability, reliability, and maintainability in mind
• Clear and precise written and verbal communication skills
• Strong documentation practices to ensure reproducibility and knowledge transfer
• Ability to mentor and guide junior analysts or engineers on technical best practices

• Microsoft Azure data services (e.g., Azure Data Factory, Azure SQL, Azure Storage)
• Data orchestration and transformation platforms
• Business intelligence and visualization tools (e.g., Power BI)
• Modern data platform services (e.g., Microsoft Fabric, data lake architectures)
• Streaming or near-real-time data processing frameworks

• Experience contributing to long-term data strategy or roadmap planning
• Experience implementing formal data governance, lineage, or data quality programs
• Experience supporting executive decision-making with structured, high-impact analysis
• Demonstrated ability to evaluate technical tradeoffs and guide architectural decisions