Data Engineer

Raising The Village

. Design and deliver batch and streaming data pipelines ingesting data from SurveyCTO, ArcGIS, and custom mobile apps into RTV's Databricks warehouse .

Posted 9/24/2026full-timeMbarara • UgandaJuniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and delivering data pipelines using PySpark and Databricks, with a strong focus on ETL/ELT workflows and data observability. Proficient in building Delta Lake tables and collaborating with cross-functional teams to ensure data quality and governance.

Highest-signal resume keywords

Python ProficiencyPySpark ExpertiseAdvanced SQL SkillsDatabricks ExperienceDelta Lake Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETL/ELT Pipeline DevelopmentData Pipeline DesignData TransformationData IntegrationData Quality ChecksSchema DesignData ObservabilityBatch ProcessingStreaming Data ProcessingGit-based Workflows

Soft Skills

CollaborationOwnershipProblem SolvingCommunication

Tools & Technologies

DatabricksDelta LakeUnity CatalogPower BITableauGreat ExpectationsDbtAWS

Industry Keywords

Data EngineeringMedallion ArchitectureData GovernanceData LineageSLA Monitoring

Tech Stack

Tools & technologies

AWSETLPandasPySparkPythonSparkSQLTableauUnity

About the role

Key responsibilities & impact

Design and deliver batch and streaming data pipelines ingesting data from SurveyCTO, ArcGIS, and custom mobile apps into RTV's Databricks warehouse
Implement ELT and ETL workflows in PySpark and Databricks SQL using Bronze, Silver, and Gold Medallion Architecture layers
Own pipeline workstreams from design through deployment and monitoring
Build and maintain Delta Lake tables with schema enforcement, ACID-compliant writes, and time-travel capabilities
Contribute to star schema design, slowly changing dimension patterns, and denormalization decisions
Support Unity Catalog governance, lineage tracking, access controls, and dataset documentation
Maintain data observability frameworks covering freshness, volume anomalies, schema drift, and SLA monitoring
Build validation and quality checks using Great Expectations, dbt tests, or Databricks-native monitoring
Contribute to structured logging, alerting, and incident response practices
Integrate household data, image classification outputs, and ML predictions into unified warehouse layers
Collaborate with ML Engineers and Data Scientists on feature engineering and training data preparation workflows
Collaborate on roadmap prioritization, architectural decisions, and engineering standards
Partner with Software Engineers, Data Scientists, field evaluation teams, and program staff to translate data requirements into pipeline solutions
Maintain documentation covering pipeline architectures, transformation logic, data dictionaries, and runbooks

Requirements

What you’ll need

1–3 years of experience
Bachelor's degree in Computer Science, Software Engineering, Data Engineering, Information Systems, Statistics, or a related quantitative field is preferred
Equivalent practical experience through demonstrable project work, open-source contributions, or bootcamp training is equally welcome
Clear evidence of building and shipping production-grade pipelines, with ownership from design through deployment
Demonstrable experience integrating, moving, and transforming data at meaningful scale
Proficiency in Python, including Pandas
Proficiency in PySpark
Proficiency in advanced SQL
Experience building or supporting ETL/ELT pipelines
Experience working in a Databricks-first environment
Proficiency with Delta Lake, Unity Catalog, and Medallion Architecture
Experience with batch and Spark Structured Streaming pipelines
Data observability experience covering validation, monitoring, and alerting frameworks
Git-based collaborative workflows
Working knowledge of AWS core services
Ability to produce clean, visualization-ready datasets for Power BI, Tableau, or Python visualization libraries

Benefits

Comp & perks

Equal opportunities and diversity of perspective at the workplace
Encouragement for women, people with disabilities, and minority groups to apply