Senior Data Engineer - Data Pipelines, Analytics & AI/ ML

Looking for a skilled Data Engineer III to design, develop, and maintain scalable data solutions for integrating, processing, and analyzing large volumes of structured and unstructured data from diverse sources.

The role involves leveraging advanced analytics, statistical techniques, and artificial intelligence (AI) and machine learning (ML) solutions to address complex business problems, generate actionable insights, and support data-driven decision-making.

The ideal candidate will be responsible for designing databases and data models, optimizing data pipelines, conducting exploratory data analysis, and developing reports, dashboards, and analytical datasets to support business objectives.

The role also requires close collaboration with data analysts, data engineers, and business stakeholders to improve data quality, enhance data processing efficiency, and deliver measurable business value. Required Education Bachelor’s degree required, preferably in engineering, mathematics, computer science, or business.

Required Qualifications

• Strong knowledge of data engineering concepts, data integration, data processing, and data management.
• Experience working with large, complex, structured, and unstructured datasets from multiple sources.
• Proficiency in database design, data modeling, data querying, and data warehouse technologies.
• Experience developing, maintaining, and optimizing data pipelines and data processing workflows.
• Knowledge of advanced analytics, statistical methods, exploratory data analysis, and data interpretation.
• Ability to identify trends, patterns, and correlations across diverse datasets to address complex business problems.
• Understanding of data transformation, data cleansing, and data preparation techniques for statistical analysis and downstream consumption.
• Knowledge of machine learning and artificial intelligence concepts, including the ability to develop or define solutions that address business needs.
• Experience generating reports, dashboards, datasets, and other data-driven resources to support business decision-making.
• Strong analytical thinking, problem-solving, and data-driven decision-making skills.
• Ability to translate complex business requirements and technical designs into scalable data and AI solutions.
• Effective communication and collaboration skills to work with data analysts, data engineers, and business stakeholders.
• Ability to provide technical guidance and feedback on data quality, pipeline development, and optimization opportunities.

Job Responsibilities

Design, develop, and maintain processes and systems to consolidate data from multiple structured and unstructured sources. Integrate data from diverse internal and external systems to produce required data elements for business and analytical use cases. Design databases and data models for unstructured datasets, defining how data will be stored, consumed, integrated, and managed.

Develop and maintain data pipelines and data processing workflows to ensure data availability, consistency, and usability. Identify and implement opportunities to optimize data integration, processing, and storage. Address complex business problems by applying advanced analytics techniques to large, unstructured datasets.

Conduct exploratory data analysis using complex data sources and develop key datasets to support business insights. Apply advanced mathematical and statistical concepts to collect, analyze, and interpret data. Identify trends, patterns, and correlations across disparate datasets to uncover actionable insights.

Develop analytical approaches to investigate potential drivers and relationships between data variables. Transform, clean, and prepare data into appropriate formats for statistical analysis and analytical modeling. Generate reports, recurring datasets, and analytical outputs for end users using system tools, database queries, data warehouse queries, and scripts.

Gather business reporting requirements and translate them into report specifications and data deliverables. Develop and maintain reports, information dashboards, canned reports, data generators, and end-user data portals. Ensure that reports and datasets provide accurate, relevant, and actionable information to support business decisions.

Build or define machine learning and artificial intelligence solutions that create measurable business value. Translate complex business requirements and technical designs into data science and AI solutions aligned with organizational goals. Identify opportunities to apply AI, machine learning, and advanced analytics to improve client services, products, and business processes.

Develop data foundations and analytical datasets that support AI and machine learning applications. Collaborate with data analysts and data engineers to review data pipelines and identify opportunities for improvement. Provide feedback and recommendations on data pipeline design, performance, data quality, and optimization.

Guide and support data transformation and cleansing activities to ensure datasets are suitable for analytical use. Work with relevant stakeholders to understand business challenges and deliver data solutions that meet functional and technical requirements. Analyze complex business issues using data from internal and external sources and provide insights to decision-makers.

Convert business challenges into analytical approaches, technical solutions, and actionable recommendations. Ensure that data engineering, analytics, and AI initiatives align with business objectives and deliver measurable organizational value. Support product enhancement and client service improvements through data-driven insights and solutions.

Only those lawfully authorized to work in the designated country associated with the position will be considered. Please note that all Position start dates and duration are estimates and may be reduced or lengthened based upon a client’s business needs and requirements. About Rose Founded in 1993 Office Locations Across the U.S.

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