Senior Data Engineer
Hybrid Cairo Full-time Senior Data Engineering
At a glance
Senior Data Engineering role at Bosta. Cairo · full-time.
Pay not stated Data Engineer salary
RoleData Engineering
SenioritySenior
LocationCairo
WorkplaceHybrid
EmploymentFull-time
PostedMay 25, 2026 · 5mo ago
Role brief
dataroles summary, based on the employer's posting.
What you'll do
- Build data flows from MongoDB change capture through ingestion, the lakehouse, warehouse, dbt, and BI or AI tools
- Help shape architecture with the Data Engineering Lead and establish reusable ingestion patterns for new sources
- Keep production database load in check while making change-data capture and orchestration observable
- Set dbt conventions, tests, contracts, exposures, and CI, then maintain the project structure
- Create governed metric definitions and prepare data for AI with documentation, privacy tags, cost controls, and SQL evaluations
What you bring
- At least four years across data engineering or analytics engineering, with meaningful work on both sides
- You have led a substantial dbt and SQL project and can move between CDC connectors and dbt models
- Production CDC experience with an operational database, plus deep knowledge of a cloud warehouse
- Strong Python skills, with working ability in Linux, infrastructure as code, and CI/CD
- You understand how RAG, natural-language SQL, and embedded agents use data platforms
Who this fits
This suits a hands-on senior engineer who can work across the pipeline, from CDC and ingestion to governed metrics and AI-facing interfaces. The role is based in Cairo, Egypt, with a hybrid setup.
From the employer
About Bosta:
Launched in 2017, Bosta is an overnight delivery provider for E-commerce companies in Egypt. Leveraging technology to empower businesses is what we do best. Our goal is to disrupt the logistics industry by bringing technology and experience all together to provide a one-stop-shop for delivery solutions. We rely on advanced technology to deliver orders to our customers in a fast way. Businesses can track and connect with couriers and follow up on their orders - all in one system.
About the role:
We’re rebuilding Bosta’s data platform end-to-end: from MongoDB at the source, through a governed semantic layer that LLM-native tools (NL-to-SQL agents, AI analysts, embedded copilots) can sit on top of safely and cheaply. You will help own that rebuild.This is a hands-on role. You’ll set patterns, write the foundational code, and ship across the stack — from CDC and ingestion through dbt, the semantic layer, and the interfaces that BI tools and AI agents consume.
Launched in 2017, Bosta is an overnight delivery provider for E-commerce companies in Egypt. Leveraging technology to empower businesses is what we do best. Our goal is to disrupt the logistics industry by bringing technology and experience all together to provide a one-stop-shop for delivery solutions. We rely on advanced technology to deliver orders to our customers in a fast way. Businesses can track and connect with couriers and follow up on their orders - all in one system.
About the role:
We’re rebuilding Bosta’s data platform end-to-end: from MongoDB at the source, through a governed semantic layer that LLM-native tools (NL-to-SQL agents, AI analysts, embedded copilots) can sit on top of safely and cheaply. You will help own that rebuild.This is a hands-on role. You’ll set patterns, write the foundational code, and ship across the stack — from CDC and ingestion through dbt, the semantic layer, and the interfaces that BI tools and AI agents consume.
Job Responsibilities
- End-to-end pipeline work: MongoDB CDC → ingestion → lakehouse → warehouse → dbt → semantic layer → BI/AI consumers
- Co-ownership of architecture decisions with the Data Engineering Lead
- CDC from production MongoDB without degrading operational DB performance; ingestion patterns that make adding a new source a config change, not a project
- Orchestration that’s observable end-to-end (Airflow, Dagster, or Prefect)
- The dbt project: structure, conventions, tests, contracts, exposures, CI
- The semantic / metrics layer (dbt Semantic Layer, Cube, or equivalent) — one canonical definition per business metric
- LLM-readiness: column-level documentation, PII tagging, query cost guardrails, materialized metric tables, and evals on AI-generated SQL
- Migration of existing logic out of the Tableau and Metabase sprawl into modeled, governed sources
Job Qualifications
- 4+ years across data engineering and/or analytics engineering — you’ve spent meaningful time on both sides
- Comfort spanning the stack: comfortable shipping a Debezium connector one week and a dbt mart the next
- Deep dbt and SQL — you’ve owned a non-trivial project, not just contributed to one
- Production CDC experience (Debezium, Kafka Connect, Airbyte, or hand-rolled) against operational databases — bonus if that database was MongoDB
- A cloud warehouse you know deeply (Redshift, Snowflake, BigQuery, or Databricks)
- Strong Python; comfortable in Linux, infra-as-code, and CI/CD
- Working understanding of how LLM tooling (RAG, NL-to-SQL, embedded agents) consumes a data platform — and what breaks when the platform isn’t ready
- Strong opinions on modeling, lightly held; bias toward observability Bonus:
- MongoDB schema evolution at scale
- Production semantic-layer rollouts (dbt Semantic Layer, Cube, LookML, MetricFlow)
- Lakehouse formats (Iceberg, Delta, Hudi) or streaming experience (Kafka, Flink, Kinesis)
- Data catalog / lineage tooling (DataHub, Atlan, Collibra)
- Logistics, marketplaces, or other operationally heavy domains
- Evals on AI-generated SQL or analytical reasoning
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