Senior Data Engineer  ·  London, UK

Ghulam
Mustafa
Muhammad

Building pipelines that businesses can actually trust.

Started in consultancy. Stayed on merit. Promoted to senior in two years. I design and build robust data infrastructure — from ETL pipelines and streaming ingestion to Unity Catalog migrations and modernising legacy workflows.

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About

The engineer who
never left.

I started my career in consultancy, but on my first client deployment I never left — retained as a junior data engineer and promoted to senior within two years. That story says a lot about how I work.

I take ownership of problems end-to-end. I don't just write notebooks — I think about maintainability, observability, and what happens six months after I've shipped something. My manager's words: hardest working, best engineer on the team.

I'm language-agnostic and cloud-comfortable. Give me a messy legacy process and I'll give you something clean, documented, and built to last.

Promoted to senior in 2 years — faster than the typical 3–4 year progression.
First to production on Unity Catalog — led the migration with no internal blueprint to follow.
Consultancy to in-house — retained by the client after day one. Still building.
End-to-end ownership — from pipeline design and ingestion through to staging layers and downstream use cases.
Projects

What I've shipped.

01 Production

Unity Catalog Migration

Led the first production Unity Catalog migration at enterprise scale — with no internal blueprint to follow. Converted critical pipelines from legacy to UC, establishing the pattern used by the team going forward.

Databricks Unity Catalog PySpark Delta Lake
02 Production

Orchestrated API Ingestion Framework

Built an end-to-end ingestion framework on a newly released third-party API. Hourly jobs resolve download endpoints, ingest data, and log every run to a central audit table — providing full pipeline observability across all downstream consumers.

Databricks Python REST API Delta Lake ADF
03 Production

Config-Driven Pipeline Framework

Designed a YAML-configured notebook that allows tables to be added or removed from audit pipelines without touching code. Built to support post-acquisition data integration — a single config file drives the entire process.

Databricks YAML Delta Share Python
04 In Progress

Redaction & Retention Modernisation

Consolidating a fragmented redaction and retention process — previously spread across ADF, multiple notebooks and SSMS lookup tables — into a single, seamless Databricks workflow. Replacing complexity with clarity.

Databricks ADF SQL Python SSMS
Skills

What I bring
to the table.

Languages & Tools

  • Python
  • PySpark
  • SQL / T-SQL
  • SSMS

Platforms & Storage

  • Databricks
  • Azure Data Factory
  • Databricks Asset Bundles
  • Snowflake
  • Azure

Data & Practices

  • ETL / ELT Pipelines
  • Streaming Pipelines
  • Medallion Architecture
  • Delta Lake
  • Power BI
  • Azure DevOps
  • Git
Contact
Get
in touch

If you have a project or role that you think might be a good fit, feel free to reach out and we can have a conversation.