About Shega

Shega is building Africa’s and Emerging Markets Leading Intelligence Platform, a product that enables decision-makers across business, finance, and development sectors to access trustworthy, contextual, and AI-powered data and insights. Think of it as a Bloomberg + Palantir, purpose-built for Africa and other emerging markets.

We operate at the intersection of data, media, and intelligence. Our platform combines:

• Clean, standardized economic and business data
• AI-powered tools for querying, forecasting, and interpreting trends
• A real-time content engine that contextualizes market events and news

We're backed by trusted partners and work with leading Companies, DFIs, investors, and startups. This is a chance to build core infrastructure for how the continent and beyond makes decisions.

Role Overview:

We are seeking a Senior Data & ML Engineer to lead the development of Shega’s AI-powered data and intelligence infrastructure. You will design, build, and scale data pipelines, ML-driven features, and conversational analytics capabilities that power Shega Insights and enterprise offerings.

This role sits at the intersection of big data engineering, applied ML, and product innovation, and is critical to ensuring Shega delivers reliable, scalable, and intelligent data products for Africa’s fast-growing markets.

Key Responsibilities:

Data Engineering:

• Architect and maintain data pipelines (ETL/ELT) to process structured/unstructured data from diverse sources (government portals, APIs, financial reports, media).

• Manage Shega’s data lakehouse (Bronze → Silver → Gold layers, Delta tables) ensuring accuracy, timeliness, and accessibility of datasets.

• Build APIs and connectors for internal and external data integration.

• Implement data governance, security, and quality assurance frameworks.

Machine Learning & AI:

• Develop and optimize ML models for forecasting, entity matching, classification, and anomaly detection.

• Contribute to Shega’s AI analyst intelligence platform using ARAG Agentic (retrieval-augmented generation), embeddings, and NLP techniques.

• Experiment with conversational analytics for time-series and numerical data.

• Deploy ML models into production with MLOps best practices (CI/CD, monitoring, retraining).

Product Collaboration:

• Work closely with product managers, analysts, and business teams to define data-driven features (e.g., chart insights, research augmentation, economic indicators).

• Translate business problems into scalable ML solutions and ensure high impact on Shega’s core products.

• Support the build-out of Shega Pro and Shega Enterprise intelligence tiers.

Leadership & Mentorship:

• Provide technical leadership and mentor junior data engineers and ML engineers.

• Contribute to establishing Shega’s engineering best practices in AI, data engineering, and scalable system design.

• Stay ahead of industry trends (GenAI, data infra, vertical AI) and propose new applications for Shega’s platform.

Requirements:

Must-Have

• 5+ years of experience in data engineering and applied ML, preferably in fintech, information services, or enterprise SaaS.

• Strong proficiency in Python, SQL, PySpark, and ML frameworks (TensorFlow, PyTorch, Scikit-learn).

• Experience with cloud platforms (Azure preferred, AWS/GCP acceptable) and data infrastructure tools (Databricks, Delta Lake, Airflow, DBT).

• Hands-on experience with RAG pipelines, embeddings, and LLM integration for AI products.

• Solid knowledge of MLOps practices: model versioning, monitoring, and deployment.
  

• Familiarity with data visualization and BI tools (PowerBI, Superset, or similar).

Nice-to-Have

• Background in economics, finance, or emerging markets.

• Experience building chatbots or conversational AI (LangChain, Rasa, etc.).

• Knowledge of multilingual NLP (Amharic, or other African languages).

• Previous startup or fast-growth environment experience.

What We Offer

• Opportunity to shape Africa’s next-generation data and intelligence platform.

• Work on cutting-edge AI and ML applications with massive societal impact.

• Collaborative, mission-driven, and growth-focused team culture.