Data Analytics Engineer (Puerto Rico)

RTX•Santa Isabel, PR

5d•Remote

About The Position

The Data & Insights team in RTX Corporate is seeking a Data Analytics Engineer to develop reliable, scalable data and analytics solutions that improve business performance, operational efficiency, and decision-making. This role is responsible for integrating and transforming complex data from multiple sources, building trusted datasets and data pipelines, and applying analytical methods to solve business challenges. Working closely with stakeholders, the engineer will deliver data products, analytical solutions, and data models that drive informed decisions and support the team's AI/ML initiatives through data preparation, feature engineering, and scalable engineering solutions. The ideal candidate combines strong data engineering and analytical expertise with curiosity, critical thinking, and problem-solving skills, is comfortable navigating ambiguity, proactively partners with stakeholders to understand business needs, communicates complex data effectively to diverse audiences, and contributes technical leadership while owning projects from requirements through implementation in a fast-paced, collaborative environment.

Requirements

A University Degree or equivalent experience and minimum 8 years prior relevant experience, or an Advanced Degree in a related field and minimum 5 years experience
5+ years of experience working in data engineering, data analytics, business intelligence, or a related technical discipline.
Experience working with Python and SQL, with hands-on experience using PySpark or comparable distributed data-processing technologies.
Demonstrated experience designing and developing production-quality data pipelines, data models, ETL/ELT processes, and data integration solutions.
Experience with data quality, data governance, data warehousing, data modeling, and modern cloud data architectures.
Experience analyzing complex datasets, developing meaningful metrics and visualizations, and translating findings into actionable insights and recommendations.
Experience independently owning technical projects and delivering solutions with limited day-to-day direction, including the ability to work through ambiguous or complex problems.
Experience preparing, structuring, and curating data to support machine learning, AI/ML, advanced analytics, or other data science applications.

Nice To Haves

Experience with technologies such as Azure, Databricks, Snowflake, Delta Lake, Power BI, ServiceNow/ITSM data, Git/CI/CD, or machine learning platforms.
Strong problem-solving, communication, technical documentation, stakeholder-management, and cross-functional collaboration skills.

Responsibilities

Design, build, and maintain reliable, scalable data pipelines, data models, and curated datasets supporting analytics, reporting, decision-making, and AI/ML applications.
Integrate, transform, standardize, and validate data from diverse and 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 that improve understanding of enterprise and infrastructure data.
Establish and improve data quality, validation, monitoring, governance, documentation, and data management practices to ensure trusted and reusable data.
Work directly with customers and stakeholders to understand business and operational needs, identify opportunities for improvement, and translate requirements into practical data and analytical solutions.
Independently lead projects using appropriate software development and agile practices, from requirements and solution design through development, testing, implementation, and continuous improvement.
Develop 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 with cross-functional teams across IT and operations while providing technical guidance, peer review, and mentoring to other members of the Data & Insights team.
Apply information security, information assurance, governance, privacy, and compliance requirements to all data, analytics, and AI/ML-related activities.
This position will reference written work instructions for guidance with daily job activities. Work instructions are available in English only.