Data Analytics Engineer

This Data Analytics Engineer role focuses on building dependable data pipelines, models, datasets, and analytics solutions that support business performance and AI/ML initiatives.

Responsibilities

• Design, build, and maintain reliable, scalable data pipelines, data models, and curated datasets for analytics, reporting, decision-making, and AI/ML use.
• Integrate, transform, standardize, and validate data from diverse, non-standard sources including enterprise applications, spreadsheets, databases, text files, APIs, and operational data sources.
• Develop and maintain data visualization, statistical analysis, reporting, and analytical solutions to improve understanding of enterprise and infrastructure data.
• Establish and improve data quality, validation, monitoring, governance, documentation, and data management practices for trusted and reusable data.
• Partner with customers and stakeholders to understand business and operational needs, spot opportunities for improvement, and translate requirements into practical data and analytical solutions.
• Independently lead projects using appropriate software development and agile practices, covering requirements and solution design through development, testing, implementation, and continuous improvement.
• Create and maintain technical and business documentation, including requirements, data definitions, process flows, use cases, user stories, technical designs, and operational procedures.
• Provide data engineering and analytical support for AI/ML initiatives, including data preparation, feature development, dataset creation, experimentation support, evaluation, and integration of AI/ML outputs into operational solutions.
• Collaborate cross-functionally across IT and operations, providing technical guidance, peer review, and mentoring within the Data & Insights team.
• Apply information security, information assurance, governance, privacy, and compliance requirements across data, analytics, and AI/ML activities.
• Use written work instructions as guidance for daily job activities.

Requirements

• Education: University Degree (or equivalent experience); Advanced Degree in a related field (alternative).
• Experience: Minimum 8 years prior relevant experience (or 5 years with an Advanced Degree in a related field).
• 5+ years of experience in data engineering, data analytics, business intelligence, or a related technical discipline.
• Hands-on experience with Python and SQL, including PySpark or comparable distributed data-processing technologies.
• Proven experience designing and developing production-quality data pipelines, data models, ETL/ELT, and data integration solutions.
• Experience with data quality, data governance, data warehousing, data modeling, and modern cloud data architectures.
• Ability to analyze complex datasets, develop meaningful metrics and visualizations, and translate results into actionable insights and recommendations.
• Experience independently owning technical projects and delivering solutions with limited day-to-day direction, including working through ambiguous or complex problems.
• Experience structuring and curating data to support machine learning, AI/ML, advanced analytics, or other data science applications.

Technologies

• Python
• SQL
• PySpark
• ETL/ELT
• Azure
• Databricks
• Snowflake
• Delta Lake
• Power BI
• ServiceNow/ITSM data
• Git/CI/CD

Benefits

• Healthcare
• Wellness
• Retirement
• Work/life benefits
• Parental (including paternal) leave
• Flexible work schedules
• Achievement awards
• Educational assistance
• Child/adult backup care

U.S. Citizenship Requirements

• U.S. citizenship is required, as only U.S. citizens are authorized to access information under this program/contract.

Security Clearance

• None/Not Required

Location and Remote Details

• Remote role (primarily offsite from home).
• Successful candidate must be currently living in Puerto Rico.
• May be expected to travel to the Santa Isabel site location as needed.