Senior Data Engineer

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PATH

1001 - 5000 employees

Founded 1977

đź’° Grant - PATH on 2025-07

PATH is a global nonprofit dedicated to health equity. With nearly 50 years of experience forging multisector partnerships, and with expertise in science, economics, technology, advocacy, and dozens of other specialties, PATH develops and scales up innovative solutions to the world’s most pressing health challenges.

đź“‹ Description

• Collaborate with business and technical stakeholders to understand data requirements and develop modern data solutions • Design, build, and maintain scalable data pipelines across on-premises and cloud platforms • Develop, optimize, and maintain dimensional and other data models for analytics and reporting • Integrate data from relational databases, NoSQL platforms, APIs, and files • Enhance ETL/ELT processes through optimization, automation, and performance tuning • Develop and operate end-to-end ETL/ELT workflows with validation, error handling, logging, monitoring, and scheduling • Automate data pipeline deployment and operations through CI/CD practices • Support governance of enterprise data platforms, data lakes, data warehouses, security controls, and access management • Prepare curated data marts and fact/dimension tables to support analytics • Analyze datasets to identify trends, patterns, and anomalies • Develop interactive Power BI dashboards and reports and monitor key performance indicators • Build predictive or descriptive models using statistical, Python, or R-based methods • Present findings to non-technical audiences and translate complex data into actionable recommendations • Deliver analytics solutions iteratively in an Agile environment • Mentor teams to enhance analytics fluency and support self-service capabilities • Provide data-driven analysis, visualizations, and AI-enabled insights for strategic decision-making

🎯 Requirements

• Strong foundation in data engineering practices • Analytical skills to derive actionable insights from complex datasets • Experience designing, building, and maintaining scalable data pipelines • Knowledge of Azure, Databricks, Microsoft Fabric, GCP, and AWS • Experience with dimensional data models, including star and snowflake schemas • Experience integrating relational databases, NoSQL platforms, APIs, and files • Knowledge of AI-enabled data integration techniques, schema discovery, metadata enrichment, and automated data quality validation • Experience with ETL/ELT optimization, automation, and performance tuning • Experience with SSIS, Azure/Fabric Data Factory, Dataflows, and Notebooks • Knowledge of CI/CD, automated testing, release management, and monitoring • Knowledge of data lakes, data warehouses, security controls, and access management • Proficiency in DAX, Python, and R • Experience developing Power BI dashboards and reports • Experience building predictive or descriptive statistical or machine-learning models • Experience delivering solutions in an Agile environment

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