Data Engineer at Living Goods

Nairobi, , Kenya -

Full Time

Start Date

Immediate

Expiry Date

24 Apr, 26

Salary

0.0

Posted On

24 Jan, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, SQL, Python, ETL, Data Warehousing, Data Modeling, Data Governance, Cloud Solutions, BI Tools, CouchDB, PostgreSQL, Airflow, AWS Redshift, Snowflake, Data Quality, Data Pipelines

Industry

Non-profit Organizations

Description

Data Engineer Reports to: Senior Manager - Data Engineering & Architecture. Location: Nairobi, Kenya About Living Goods Living Goods endeavours to improve access to essential healthcare services in underserved regions, particularly in sub-Saharan Africa. We empower Community Health Workers (CHWs) with digital tools that enable them to deliver door-to-door care. CHWs use a mobile app to track pregnancies, diagnose and treat common infectious diseases like malaria and pneumonia, monitor disease outbreaks, and follow up with families. Real-time data also supports performance monitoring and impact assessment. By integrating tech-based solutions into community health systems, Living Goods fosters better health outcomes, demonstrating the power of digital health in transforming healthcare delivery in resource-constrained settings. Purpose of the role: We are looking for a Data Engineer to participate in the design, development, and management of our data warehousing infrastructure. This role involves building and maintaining data pipelines, managing both relational and non-relational databases, optimizing queries, and transforming raw data into structured data for analysis and reporting. The successful candidate will collaborate closely with the program, MLE, product management, and software engineering teams to understand data requirements and oversee the implementation of suitable solutions to ensure stakeholders’ needs are satisfied. Embedded within the Digital Health Team, this role will report to the Senior Manager, Data Engineering & Architecture. The ideal candidate will bring extensive expertise in Transactional Databases, Data Warehouses, and BI reporting systems. Roles And Responsibilities Participate in the design, implementation, and maintenance of data pipelines by performing extraction, transformation, and loading activities from structured and unstructured data sources into a data warehouse. Design and Build Data models – star schema, snowflake. Understand common analytical data models like Kimball. Build physical data models and align with best practices and requirements. Design, develop, and optimize complex SQL queries to support data discovery, analysis, and reporting. Leverage SQL to ensure accurate data staging and transformation processes that align with business requirements. Conduct thorough data discovery to identify and address data quality issues, ensuring that the data is accurate, complete, and accessible for business needs Monitor system logs for errors and performance issues; troubleshoot and resolve issues as they arise. Conduct day-to-day system checks and maintenance tasks to ensure system availability. Develop BI technical documentation – data dictionaries, definitions, data flows, database schemas, data model diagrams, Entity Relationship Diagrams (ERDs), etc. Collaborate with BI developers and users to understand business rules, capture requirements, develop user stories and write technical/functional specifications based on conceptual design and stated business requirements. Assist across internal teams to define excellence in data governance, privacy, and security. Skills & Competencies 3+ years experience as a Data Engineer. Demonstrated experience in implementing data pipelines/ETL into data warehouses and data querying and analysis using cloud-based solutions such as AWS Redshift or Snowflake. Proficiency in SQL & Python for advanced querying, data manipulation, and performance optimization. Experience with ETL tools like AWS Glue, Airbyte or Talend for building automated data pipelines. Strong knowledge of data modeling and transformation using tools like dbt. Hands-on experience with workflow automation tools such as Airflow. Expertise in managing CouchDB or PostgreSQL databases, including schema management, performance tuning, and complex queries. Extensive data warehouse experience, with skills in performance tuning, query optimization, indexing, and data integrity management. Proficiency in using BI tools such as Tableau, Power BI, or Superset for creating reports and dashboards. Strong understanding of data governance, security, and compliance best practices in cloud environments. Soft Skills: Teamwork, Collaboration, Problem solving, Strong communication and presentation skills to effectively translate technical concepts to business stakeholders. Minimum Qualifications A Bachelor’s degree in computer science, Data Science, Statistics, Mathematics, or a related discipline. Professional certifications or equivalent experience in data management, ETL processes, data warehousing, data visualization, and managing large and complex datasets. Compensation A competitive salary and benefits package commensurate with experience including health insurance and bonus opportunity. The opportunity to be your best while making lives better for those in need. Living Goods is an equal opportunity employer and will consider every qualified applicant for employment. Living Goods does not discriminate based on race, ethnicity, national origin, ancestry, religion, gender, sexual orientation or disability. Our current job openings are displayed on our website, where you can search for open positions and apply directly. Living Goods does not offer any positions without an interview and never asks candidates for money. If you are asked for money, we strongly recommend that you do not respond and do not send money or personal information.

Responsibilities

The Data Engineer will design, develop, and manage data warehousing infrastructure, including building and maintaining data pipelines. They will collaborate with various teams to understand data requirements and implement solutions to meet stakeholders' needs.