Professional Data Engineering Specialist

A Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and infrastructure to ensure efficient data collection, storage, and processing. This role involves developing and optimizing ETL (Extract, Transform, Load) processes to transform raw data into usable formats for analytics and reporting. The Data Engineer collaborates with cross-functional teams to understand data requirements and deliver solutions that support business objectives. Proficiency in programming languages such as Python or Scala, along with expertise in SQL, is essential. Additionally, experience with big data technologies like Hadoop, Spark, or Kafka, as well as cloud platforms such as AWS, Azure, or GCP, is typically required. Strong problem-solving skills and the ability to work in a fast-paced environment are also critical for success in this position. Raising The Village seeks a dedicated professional to empower rural communities through sustainable development initiatives. The ideal candidate will possess a minimum of five years of experience in international development, community engagement, or a related field, along with a deep understanding of participatory approaches. Proficiency in project management, monitoring and evaluation, and grant writing is essential, as is fluency in English, with additional language skills considered an asset. Responsibilities include designing and implementing community-led projects, fostering partnerships with local stakeholders, and ensuring alignment with organizational goals and donor requirements. The role demands strong analytical, communication, and problem-solving abilities, alongside a commitment to gender equality, social inclusion, and environmental sustainability. Mbarara The position is within a nonprofit organization and non-governmental entity, focusing on delivering mission-driven services and initiatives. Candidates must exhibit a strong dedication to the organization’s values and objectives, coupled with the ability to contribute meaningfully to its strategic goals. Responsibilities include program development, stakeholder engagement, resource mobilization, and operational oversight to ensure effective and sustainable impact. Proficiency in project management, analytical skills, and cross-functional collaboration are essential, along with excellent communication and leadership capabilities. Computer & IT, Science & Engineering, Business Operations, and Social Services & Nonprofit professionals contribute to innovation, problem-solving, and organizational growth across diverse industries. These roles demand technical expertise, analytical thinking, and adaptability to evolving challenges, whether in technology-driven fields, engineering disciplines, operational management, or mission-based organizations. Candidates should possess strong problem-solving abilities, effective communication skills, and a commitment to continuous learning, with proficiency in relevant tools and methodologies. Responsibilities include project execution, data analysis, stakeholder collaboration, and strategic decision-making, tailored to the specific sector’s objectives and ethical considerations. We seek a skilled Data Engineer to join our Venn team, reporting directly to the Senior Data Scientist. This role requires 1 to 3 years of relevant experience and is based in Barbara, with an anticipated 20% travel commitment. As a dynamic international development organization and registered charity, Raising The Village (RTV) is dedicated to eradicating ultra-poverty across sub-Saharan Africa. With a rapidly expanding footprint, RTV currently employs over 350 local staff across the SSA region and maintains a 15-person team in North America, collaborating to uplift communities in remote, underserved villages. Our unique approach integrates hands-on implementation with cutting-edge data analytics, enabling us to track progress, guide strategic decisions, and maximize sustainable impact. We have successfully assisted over one million individuals across Sub-Saharan Africa through our comprehensive, integrated approach, with plans to further broaden our influence and effectiveness annually. We attribute our remarkable expansion to the invaluable collaboration of our global partners, who share our vision and endorse our mission. Explore our initiatives and gauge our impact at www.raisingthevillage.org. The VENN department serves as the foundational data and technology infrastructure for our organization, integrating advanced analytics and tailored software solutions with practical field applications to facilitate informed decision-making across all levels. The Data Engineer serves as a key contributor to RTV’s growing data infrastructure team, reporting to the Senior Data Scientist in the VENN department. This position involves designing, developing, and maintaining critical pipelines, warehouse layers, and data quality systems that drive RTV’s programmatic analytics, machine learning platforms, and field evaluation tools. With a focus on bridging data platform engineering, ML infrastructure support, and field data integration, the role navigates a dynamic roadmap encompassing batch and streaming ingestion, ELT pipeline development, Delta Lake architecture, observability frameworks, and the seamless integration of structured field data with AI model outputs. Key Responsibilities Pipeline Development & Delivery involves designing, constructing, and maintaining efficient and reliable data pipelines to facilitate data flow between systems, ensuring seamless integration and accessibility. This role requires expertise in ETL (Extract, Transform, Load) processes, proficiency in SQL, Python, and data pipeline tools such as Apache Airflow, and strong problem-solving skills to optimize performance. Responsibilities include collaborating with cross-functional teams to gather requirements, developing scalable pipeline architectures, monitoring pipeline health, troubleshooting issues, and ensuring data integrity and security. Candidates must possess a strong understanding of cloud platforms like AWS or GCP, experience with data warehousing solutions such as Snowflake or BigQuery, and a commitment to continuous improvement and innovation in data infrastructure. Develop and uphold Delta Lake table architectures, ensuring robust schema enforcement, ACID-compliant write operations, and time travel functionality to enhance auditability across program datasets.

• Assist in shaping data modeling strategies, encompassing star schema design, Slowly Changing Dimension (SCD) methodologies, and balancing denormalization benefits against performance considerations.
• Facilitate the advancement of Unity Catalog governance frameworks, encompassing lineage tracking, access controls, and dataset documentation, as the data warehouse expands into new program domains and geographic regions. Data observability and quality specialists ensure the reliability, accuracy, and usability of organizational data by implementing monitoring systems, validating datasets, and enforcing governance policies. They analyze data pipelines to identify anomalies, discrepancies, or performance bottlenecks, and collaborate with cross-functional teams to resolve issues promptly. Proficiency in data profiling, anomaly detection, and root because analysis is essential, alongside experience with tools such as Great Expectations, Monte Carlo, or similar platforms. Strong analytical skills, attention to detail, and the ability to communicate findings clearly to stakeholders are critical for success in this role. Implement and sustain robust data observability frameworks throughout every stage of the pipeline, ensuring rigorous monitoring of data freshness, volume anomalies, schema drift detection, and adherence to service-level agreements. Develop robust validation and quality assurance frameworks at both ingestion and transformation stages, employing tools like Great Expectations, debt tests, or Databricks-native monitoring solutions to ensure data integrity and reliability. Develop and maintain standardized logging, alerting, and incident response protocols to ensure the team has immediate and dependable insights into pipeline performance across every environment. We provide essential assistance for the Machine Learning and Artificial Intelligence pipeline, ensuring seamless operation and optimization of workflows. This role involves diagnosing issues, troubleshooting technical challenges, and implementing improvements across various stages of the pipeline. Candidates must possess expertise in ML/AI frameworks, strong problem-solving skills, and the ability to collaborate effectively with cross-functional teams. Responsibilities include maintaining infrastructure, monitoring performance metrics, and enhancing system efficiency. Prior experience in a similar support capacity within ML or AI environments is required. Integrate structured household data, image classification results, and machine learning model predictions into a cohesive warehouse infrastructure, facilitating seamless access for Data Scientists and the Workmate AI platform. Collaborate closely with ML Engineers and Data Scientists to develop and sustain feature engineering pipelines and training data preparation workflows, ensuring they effectively support RTV’s computer vision and adoption scoring systems. Collaborate effectively with cross-functional teams to share insights, align on objectives, and deliver cohesive solutions, while maintaining clear and accurate documentation to support project continuity and compliance. Collaborate effectively with the Senior Data Engineer to establish and refine the roadmap, make critical architectural decisions, and uphold engineering standards throughout the team’s growth. Collaborate closely with Software Engineers, Data Scientists, field evaluation teams, and program staff to identify data requirements and develop robust, well-documented pipeline solutions. Responsibilities include creating and updating comprehensive documentation for pipeline architectures, transformation logic, data dictionaries, and run books, ensuring team scalability and preserving institutional knowledge. Must possess a degree in Computer Science, Engineering, or a related technical field, and have at least 3 years of hands-on experience in software development or system administration. Proficiency in programming languages such as Python, Java, or C++ is essential, along with experience with databases, APIs, and cloud services like AWS or Azure. Familiarity with DevOps tools, including Docker and Kubernetes, is required, and knowledge of Linux systems and networking concepts is mandatory. Strong problem-solving abilities and excellent communication skills for collaborating with cross-functional teams are also necessary. A degree in a related field and relevant professional experience are essential requirements for this role. Candidates should possess a minimum of [X] years of hands-on experience in [specific industry or function], along with a proven track record of success in [key responsibilities or achievements]. Previous tenure in

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