Data Engineer – Data Analytics, Business Intelligence

Responsibilities

• Partner with engineering, operations, program management, and business stakeholders to understand objectives, define reporting requirements, and deliver analytics solutions that support informed decision-making.

• Analyze large, complex datasets to identify trends, anomalies, performance gaps, risks, and opportunities for operational improvement.

• Conduct data quality assessments, validation, and verification activities to ensure accuracy, completeness, consistency, and integrity across multiple data sources.

• Design, implement, automate, and maintain scalable data collection, transformation, validation, and reporting processes.

• Develop and maintain dashboards, KPI scorecards, reports, and self‑service analytics solutions that provide visibility into operational performance, program health, technical metrics, and business outcomes.

• Build data validation frameworks, monitoring processes, and quality controls to proactively identify and resolve data issues.

• Collaborate with technical teams to enhance data models, reporting structures, metadata management practices, and overall data governance initiatives.

• Translate complex technical findings into clear, concise, and actionable recommendations for both technical and executive audiences.

• Drive process improvements through automation, standardization, and implementation of scalable analytics and reporting solutions.

• Support root cause investigations by leveraging data to identify drivers of operational issues, risks, and performance challenges.

• Document methodologies, business requirements, reporting processes, and data quality standards to ensure consistency and scalability.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, Information Systems, Data Analytics, or a related technical field.

• 5–7 years of professional experience in data analytics, business intelligence, reporting, data quality management, or a related discipline.

• 4+ years of experience conducting data quality validation and verification to ensure data accuracy, completeness, and consistency across multiple systems and sources.

• 4+ years of experience analyzing large datasets to identify trends, anomalies, risks, gaps, and opportunities for improvement.

• 3+ years of experience developing dashboards, reports, and visualizations using Power BI, Tableau, or similar business intelligence platforms.

• Experience designing and implementing data quality monitoring, validation, and governance processes.

• Experience automating manual workflows using scripting, workflow automation, or data integration technologies.

• Strong analytical, troubleshooting, problem‑solving, and investigative skills.

• Excellent written and verbal communication skills with the ability to present complex findings to both technical and non‑technical audiences.

• Demonstrated success delivering scalable solutions that improve operational visibility, efficiency, and data reliability.

Core Competencies

Demonstrates expertise in data analytics, data quality management, and business intelligence, with a strong focus on developing scalable reporting solutions and dashboards. Proficient in translating complex data findings into actionable insights for diverse audiences.