Senior Data Infrastructure Engineer

Responsabilités

Designs, constructs, maintains, and optimizes robust data pipelines and architectures to facilitate efficient data ingestion, processing, transformation, and storage. Develops ETL/ELT workflows to ensure data consistency, accuracy, and availability across diverse systems and databases. Implements data warehousing solutions using platforms such as Snowflake, Redshift, or BigQuery to support analytical and reporting needs. Collaborates closely with cross-functional teams, including data scientists, analysts, and software engineers, to identify data requirements and deliver scalable, high-performance solutions. Ensures compliance with data governance policies, security protocols, and regulatory standards while optimizing performance through monitoring, troubleshooting, and continuous improvement initiatives. Proficient in SQL, Python, or Scala, with hands-on experience in cloud platforms like AWS, Azure, or GCP. Raising The Village is a social enterprise committed to empowering rural communities in Sub-Saharan Africa through sustainable economic growth. By providing access to microfinance, digital tools, and capacity-building initiatives, the organization enables individuals to enhance their agricultural productivity, financial literacy, and market connectivity. Applicants should possess a passion for sustainable development, experience in project management or social entrepreneurship, and proficiency in data analysis. Fluency in English is required, while knowledge of a local language or regional experience is highly desirable. Mbarara We are seeking a dynamic professional to join our esteemed nonprofit organization, dedicated to advancing social impact and sustainable development. The ideal candidate will possess a minimum of five years of progressive experience in nonprofit management, fundraising, or a closely related field, with a proven track record of securing grants and cultivating donor relationships. Strong leadership skills, exceptional communication abilities, and a deep commitment to our mission are essential. Responsibilities include developing strategic initiatives, overseeing program implementation, managing budgets, and fostering partnerships to amplify our reach. Proficiency in grant writing, data analysis, and stakeholder engagement is required, along with a Bachelor’s degree in a relevant discipline. Computer & IT, Science & Engineering, Business Operations, Social Services & Nonprofit Seeking a skilled Data Engineer to join the Venn team, reporting to the Senior Data Scientist. The ideal candidate will possess 1 to 3 years of relevant experience and be based in Barbara, with an expected travel commitment of 20%. This role requires expertise in designing, developing, and maintaining robust data infrastructure to support analytical and operational needs. About Raising The Village We are Raising The Village (RTV), an international development organization and registered charity, committed to eliminating ultra-poverty across sub-Saharan Africa. With rapid expansion underway, RTV employs over 350 national staff in the Sub-Saharan Africa (SSA) region and a 15+ member North American team, all collaborating to uplift last-mile communities from extreme poverty. Our approach integrates hands-on implementation with sophisticated data analytics, driving progress, informed decision-making, and measurable impact. We have successfully assisted over one million individuals across Sub-Saharan Africa through our comprehensive, integrated methodology and continue to grow our influence and effectiveness annually. We’ve attained this remarkable expansion through the invaluable contributions of our global partners, who share our vision and commitment to our mission. Explore our initiatives and the lasting impact we’ve created by visiting www.raisingthevillage.org. The VENN department serves as the organization’s core data and technology infrastructure, seamlessly integrating advanced analytics and tailored software solutions with practical field applications to facilitate data-driven decision-making across all levels. The Data Engineer plays a pivotal role in constructing RTV’s growing data infrastructure, reporting directly to the Senior Data Scientist within the VENN department. This position involves designing, developing, and maintaining pipelines, warehouse layers, and data quality systems that underpin RTV’s programmatic analytics, machine learning platforms, and field evaluation tools. At the crossroads of data platform engineering, ML infrastructure support, and field data integration, the role drives progress on a dynamic roadmap encompassing batch and streaming ingestion, ELT pipeline development, Delta Lake architecture, observability frameworks, and the fusion of structured field data with AI model outputs. Oversee a diverse range of critical duties, including strategic planning, team leadership, and operational execution to ensure organizational success. Develop and implement policies that enhance efficiency, compliance, and performance across departments. Collaborate with senior management to align business objectives with evolving market demands and regulatory standards. Foster a culture of accountability, innovation, and continuous improvement through mentorship, training, and performance monitoring. Analyze key performance indicators to identify trends, mitigate risks, and drive data-informed decision-making. Manage stakeholder relationships to maintain transparency, trust, and alignment with company values. Represent the organization in external engagements, such as industry conferences, partnerships, and client interactions, to bolster brand reputation and growth opportunities. Developing and delivering robust pipelines represents a critical function within our organization. This role entails designing, constructing, and optimizing data or software pipelines to ensure seamless data flow and efficient processing. Key responsibilities include collaborating with cross-functional teams to gather requirements, implementing scalable solutions, and maintaining pipeline integrity through rigorous testing and monitoring. Candidates must possess strong proficiency in programming languages such as Python or Java, alongside experience with pipeline tools like Apache Airflow or AWS Data Pipeline. Additionally, expertise in cloud platforms (e.g., AWS, GCP) and a solid understanding of data engineering principles are essential requirements for success in this position. Construct and uphold Delta Lake table architectures, ensuring robust schema enforcement, ACID-compliant write operations, and time travel functionality to facilitate auditability across program datasets. Collaborate in shaping data modeling strategies, focusing on star schema architecture, Slowly Changing Dimension (SCD) methodologies, and balancing normalization with performance optimization through denormalization techniques. Support the development of Unity Catalog governance frameworks, emphasizing lineage tracking, access management, and dataset documentation, as the data warehouse expands into new program domains and geographic regions. At this organization, we are seeking a skilled professional to oversee Data Observability and Quality, ensuring the integrity, accuracy, and reliability of our data assets. The ideal candidate will be responsible for developing, implementing, and maintaining robust monitoring frameworks to detect anomalies, inconsistencies, and data drift in real time. Additionally, they will design and enforce quality assurance protocols, validate data pipelines, and collaborate with cross-functional teams to address data-related issues promptly and efficiently. Proficiency in data governance, regulatory compliance, and advanced analytical tools is essential, along with a strong ability to translate technical insights into actionable business strategies. This role requires a proactive approach to identifying risks, optimizing data processes, and fostering a culture of data excellence across the enterprise. Develop and sustain data observability frameworks throughout every stage of the pipeline, ensuring monitoring of data freshness, volume anomalies, schema drift detection, and adherence to service-level agreements. Develop and implement robust validation and quality assurance processes at both the data ingestion and transformation stages by leveraging tools like Great Expectations, debt tests, or Databricks-native monitoring features. Develop and implement standardized logging frameworks, alerting mechanisms, and incident response protocols to ensure the team maintains immediate, dependable oversight of pipeline performance across every environment. We provide essential assistance for Machine Learning and Artificial Intelligence pipeline operations, ensuring seamless functionality and optimal performance. This role involves maintaining and troubleshooting ML/AI workflows, addressing technical challenges, and collaborating with cross-functional teams to enhance system reliability. Responsibilities include monitoring pipeline efficiency, resolving data processing issues, and implementing improvements to support scalable AI solutions. Ideal candidates possess strong problem-solving skills, proficiency in Python or R, and experience with cloud platforms such as AWS or Azure. A background in data engineering, DevOps, or related fields is highly advantageous. Integrate structured household data, image classification outputs, and machine learning model predictions into consolidated warehouse layers, making them accessible to Data Scientists and the Workmate AI platform. Collaborate closely with ML Engineers and Data Scientists to develop, optimize, and sustain feature engineering pipelines and training data preparation workflows, ensuring robust support for RTV’s computer vision and adoption scoring systems. Demonstrates strong proficiency in teamwork and maintaining precise, thorough documentation practices. Collaborate effectively with the Senior Data Engineer to align on roadmap priorities, make key architectural decisions, and establish engineering standards in tandem with team growth. Collaborate with Software Engineers, Data Scientists, field evaluation teams, and program staff to align on data requirements and develop robust, thoroughly documented pipeline solutions. Maintain comprehensive documentation of pipeline architectures, transformation logic, data dictionaries, and run books to facilitate team expansion and ensure organizational knowledge continuity. Technical Requirements include proficiency in programming languages such as Python, Java, or C++, along with experience in database management systems like SQL or NoSQL. Candidates should possess a strong understanding of software development methodologies, including Agile and DevOps practices. Familiarity with cloud platforms, such as AWS, Azure, or Google Cloud, is essential, as is expertise in containerization technologies like Docker and Kubernetes. Additionally, knowledge of networking concepts, cybersecurity principles, and version control systems (e.g., Git) is required. Experience with API development, integration, and troubleshooting is also necessary. Seeking candidates with a Bachelor’s degree in a relevant field and at least three years of professional experience in a comparable role, preferably within [industry/field if applicable]. Familiarity with [specific tools, software, or methodologies] is required, along with strong analytical and problem-solving abilities. Experience in [specific tasks or responsibilities] is highly advantageous, as is a track record of successfully managing [relevant projects or teams]. Exceptional communication skills and the capacity to thrive in a fast-paced environment are essential. A Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, Information Systems, Statistics, or a closely related quantitative discipline is highly desirable. Equally, valuable will be relevant hands-on experience demonstrated through completed projects, contributions to open-source initiatives, or completion of an intensive bootcamp program. Demonstrably proficient in constructing and deploying production-grade data pipelines, with a proven track record of end-to-end ownership—from conceptual design to final deployment—exemplified by concrete instances of seamless data integration, efficient processing, and meaningful transformation at scale. Proficient in technical skills encompassing programming languages, software development methodologies, and system architectures. Demonstrates expertise in troubleshooting, debugging, and problem-solving within complex technical environments. Requires familiarity with cloud platforms, version control systems, and DevOps practices to ensure seamless integration and deployment processes. Must possess strong analytical abilities to interpret technical specifications and translate them into efficient, scalable solutions. Additionally, requires proficiency in database management, cybersecurity principles, and IT infrastructure optimization to support organizational objectives.

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