Data analyst/Data Engineer

Groupe SEGULA Technologies SA; Auburn (AL); On-site; USD 140,000 - 180,000; Full time

Job summary

Groupe SEGULA Technologies SA is seeking a Lead Product Development Data Engineer to own data processes across PDP, bridging Engineering with IT, Manufacturing, Finance, and Supply Chain. You will design scalable data models and modern cloud architectures, leverage Snowflake, Databricks, and Microsoft Fabric, and build executive dashboards.

This role emphasizes governance, security, and cross-functional collaboration.

Qualifications

• Experience building enterprise data platforms and pipelines.
• Familiarity with modern cloud architectures (Lakehouse, DirectLake).
• Ability to govern data quality, lineage, and security.

Responsibilities

• Develop data architectures and scalable cloud data pipelines using Snowflake, Databricks, and Fabric.
• Create BI dashboards and governance standards for executive reporting.
• Lead cross-functional teams and support AI/ML integration into data flows.

Skills

Data modeling

Cloud architectures

Big data pipelines

Cross-functional collaboration

Tools

Snowflake

Databricks

Microsoft Fabric

Power BI

PowerApps

Palantir Foundry

Power Automate

Job description

Position Summary

The Lead Product Development Data Engineer owns key data processes and analytics applications within the broader Product Development Process (PDP). In this cross-functional role, you will bridge the gap between Engineering and enterprise organizations—including IT, Manufacturing, Finance, Purchasing, and Supply Chain—to establish standardized, high-performing data workflows, modern cloud architectures, and scalable analytics solutions.

Key Responsibilities

1. Data Architecture & Cloud Engineering

• Enterprise Platform Management: Build, optimize, and maintain big data pipelines and architectures leveraging Snowflake, Databricks, or Microsoft Fabric.

• Cloud & Data Pipelines: Design scalable data models and storage solutions (Lakehouse, DirectLake) using SQL, Python, PySpark, and cloud ecosystems across Azure or AWS.

• Modern Analytics Integration: Migrate legacy data workflows to modern cloud architectures, establishing robust data governance, pipeline security, and data lineage.

2. Process Governance & Analytics Standards

• Process Ownership: Drive global uniformity, documentation, and continuous refinement across assigned Product Development processes and digital applications.

• Business Intelligence & Dashboards: Develop, deploy, and maintain executive-level dashboards and reporting tools using Power BI, PowerApps, and Palantir Foundry.

• Workflow Automation: Streamline administrative and operational cross-functional engineering tasks using Power Automate and Microsoft 365 tools.

3. Cross-Functional Leadership & AI/ML Support

• Stakeholder Alignment: Collaborate across IT, Manufacturing, Finance, Purchasing, and Program Management to capture technical requirements and align business goals.

• AI/ML Workflows: Support the integration of machine learning models and predictive analytics into existing engineering data pipelines.

• Executive Communication: Translate complex data technicalities and process trade-offs into clear decision packages, business cases, and leadership presentations.