Senior Data Engineer & Scientist - AI Platform Lead

Robertson,-Anschutz,-Schneid,-Crane-

Boca Raton (FL)

Hybrid

USD 110,000 - 170,000

Full time

10 days ago

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Job summary

Robertson,-Anschutz,-Schneid,-Crane- seeks a Senior Data Engineer & Scientist to design, build, and maintain enterprise-scale data platforms, data pipelines, analytics solutions, and AI-enabled applications that support business operations and decision-making.

Reporting to the Director of AI & Automation, the role combines data engineering, data science, analytics, and AI integration to establish a modern data ecosystem with trusted data intelligence, advanced analytics, and AI-driven insights.

Qualifications

Bachelor's degree in Computer Science, Data Science, Data Analytics, Information Systems, Engineering, or a related field (Master's degree preferred).
5+ years of professional experience in Data Engineering, Data Science, Analytics Engineering, Automation or a related technical discipline.
Proven experience designing and implementing enterprise data platforms, data warehouses, lakehouses, and scalable ETL/ELT solutions.
Strong hands-on expertise in SQL, Python, Spark, and modern cloud-based data platforms.
Experience building scalable data pipelines, enterprise data integrations, and reporting datasets.
Working knowledge of machine learning, predictive analytics, statistical modeling, and data science methodologies.
Experience supporting AI initiatives, including Generative AI, Document Intelligence, NLP, RAG, or related AI technologies.
Strong understanding of data governance, metadata management, data quality, security, and compliance principles.
Excellent analytical, problem-solving, and stakeholder communications skills.
Experience working within Microsoft Azure, AWS, or Google Cloud environments and modern DevOps practices.

Responsibilities

Design, develop, and maintain enterprise data platforms, including datalakes, warehouses, lakehouses, semantic models, and medallion architectures (Bronze, Silver, Gold).
Build and optimize scalable ETL/ELT pipelines using Azure Databricks, Azure Data Factory, Snowflake, SQL, Python, Spark, AWS, GCP.
Integrate data from internal applications, third-party systems, APIs, automation platforms, and external data sources.
Develop enterprise data models, master data structures, and reusable datasets for reporting, analytics, automation, and AI initiatives.
Support data migration, modernization, and consolidation across business applications.
Implement and maintain data governance, cataloging, lineage, data quality, auditing, observability, and security standards.
Analyze structured and unstructured data to identify trends, patterns, opportunities, and actionable insights.
Develop predictive models and ML solutions to improve operational outcomes and decision-making; create data products, dashboards, KPIs, and metrics.
Support AI initiatives including Generative AI, IDP, and Retrieval-Augmented Generation (RAG) architectures.
Prepare, curate, and optimize enterprise datasets for ML and AI workloads.
Develop and maintain data pipelines supporting LLMs, Document Intelligence, vector databases, and AI platforms.
Enable enterprise search, knowledge management, and contextual data access capabilities.
Collaborate with AI engineers to integrate AI capabilities into business applications and workflows.
Participate in full solution lifecycle from requirements through deployment and support.
Ensure compliance with security, privacy, governance, and regulatory requirements.
Monitor and optimize platform performance, scalability, reliability, and cost efficiency.
Collaborate with cross-functional teams to deliver high-quality, business-focused solutions.
Contribute to technical standards, best practices, documentation, and continuous improvement initiatives.