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FDJ UNITED

Senior Data Engineer

London
Posted about 14 hours ago
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A hands-on engineering role building and optimising scalable ETL/ELT pipelines and Lakehouse architectures across a modern multi-cloud platform using Python, Spark, Airflow, and dbt.

Requires 5+ years of data engineering experience with strong expertise in SQL, CI/CD, data quality frameworks, and cloud technologies (S3, Athena, Redshift), with a plus for streaming and AI tooling experience.

Overview

A Senior Data Engineer position within an agile team, focused on building scalable data pipelines and modernizing a multi-cloud data platform. The role involves working with streaming technologies, Lakehouse architectures, and leveraging automation/AI to improve efficiency.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Strong

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What you will do

  • Pipeline Development: Build ETL/ELT pipelines (Python, SQL), optimize Spark/PySpark jobs, manage Airflow DAGs, and implement dbt transformations.
  • Lakehouse Architecture: Design medallion-style architectures using S3 and modern table formats (Iceberg, Delta Lake) with optimized layouts.
  • Platform Infrastructure: Create reusable frameworks, enforce data contracts, build CI/CD pipelines, and establish observability practices.
  • Data Quality: Implement validation frameworks, data contracts, and SLIs/SLOs for critical pipelines.

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Your experience

Required

  • 5+ years in data engineering
  • Strong Python, advanced SQL, Airflow, Spark/PySpark, dbt, and CI/CD proficiency
  • Experience with Lakehouse architectures, dimensional modeling, and cloud data warehouses (S3, Athena, Redshift)
  • Data quality frameworks, monitoring, and schema evolution expertise

Nice-to-Haves

  • Streaming platforms (Kafka, Kinesis)
  • AI coding assistants (Cursor, Claude Code, Copilot)
  • Terraform, Kubernetes/Docker
  • Data catalog/metadata management experience

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Skills

Python
SQL
Airflow
Spark
PySpark
Dbt
CI/CD
S3
Athena
Redshift
Lakehouse Architecture
Dimensional Modeling
Kafka
Kinesis
Terraform
Kubernetes

Location

London, England, United Kingdom

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