Senior Data Engineer - Hybrid Cloud Data Pipelines & AI

Publicis Media; Greater London; Hybrid; GBP 55,000 - 95,000; Full time

Benefits offered by this job

Pension

Life assurance

Private medical

Work Abroad option

Reflection days

Help at Hand

Family-friendly policies

Flexible working

Bank holiday swap

Birthday leave

Job summary

Publicis Media is seeking a hands-on Data Engineer to shape our cloud-native data architecture. You will build and optimize ingestion and transformation pipelines, unify datasets across 20+ marketing platforms, and contribute to production codebases in Python, SQL, and Spark.

You will collaborate with product and data science teams, implement CI/CD and data governance, and mentor junior engineers while ensuring performance and reliability across pipelines.

Qualifications

• Hands-on experience as a Data Engineer or Data Platform Developer, with contributions to production codebases.
• Expert-level Python, SQL, and Apache Spark for data pipeline development.
• Proven experience building ELT workflows using Fivetran, Airflow, DBT, or Databricks.
• Solid understanding of data modeling, dimensional design, and schema normalization at scale.
• Strong experience with AWS or GCP (S3, Redshift, Glue, Lambda; BigQuery, Dataflow).
• Experience with marketing/ad platform data (Google Ads, Meta, TikTok, DV360, Amazon Ads).
• Code versioning (GitHub), CI/CD integration, and data observability practices.
• Ability to write clean, modular, testable code and review peers for maintainability and performance.

Responsibilities

• Lead hands-on design, coding, and evolution of cloud-native data architecture (AWS/GCP/Snowflake).
• Architect and implement scalable ingestion/transformation pipelines using Fivetran, Databricks, and Airflow/DBT.
• Design and code modular data services/APIs unifying datasets across 20+ marketing platforms.
• Build and optimize schemas, transformations, and ETL logic for high performance.
• Contribute to DFP codebase (Python, SQL, Spark) with pipelines and infra.
• Establish data versioning, testing, governance ensuring reliability and lineage.
• Drive best practices in data modeling, CI/CD, and performance optimization.
• Collaborate to define data contracts, schema validation, automated quality checks.
• Mentor junior engineers via pair programming, PR reviews, coaching.
• Participate in sprint planning/retrospectives to align with platform goals.
• Partner with Product/Data Science to translate analysis needs into production-grade solutions.
• Design/maintain pipelines for Retrieval-Augmented Generation (RAG) workflows.
• Build high-performance APIs and caching for low-latency AI access.
• Implement vector retrieval layers (pgVector, Pinecone) and embedding pipelines.
• Monitor data latency, cost efficiency, and observability with AI teams.
• Work with Platform Operations and Security on privacy and access controls.
• Collaborate across analysts/AI engineers to deliver business-critical data products.
• Lead documentation, testing, and lineage for reproducibility across pipelines.

Skills

Data Eng

Python

SQL

Spark

ELT Pipelines

Fivetran

Airflow

DBT

Databricks

GitHub

CI/CD

Data Modeling

AWS

GCP

Marketing Data

APIs

Code Review

Tools

Fivetran

Airflow

DBT

Databricks

Python

SQL

Spark

GitHub

Snowflake

Redshift

BigQuery

Job description

Publicis Media is seeking a hands-on Data Engineer to shape our cloud-native data architecture. You will build and optimize ingestion and transformation pipelines, unify datasets across 20+ marketing platforms, and contribute to production codebases in Python, SQL, and Spark.

You will collaborate with product and data science teams, implement CI/CD and data governance, and mentor junior engineers while ensuring performance and reliability across pipelines.