Data Platform Engineer

Lenstra was created by a passion of engineers specialised in Computer Science with a proven history in delivering top quality solutions to its customers.

Bringing together work excellence and vision we managed to serve top tier clients from a variety of industry domains like Banking/Insurance, Luxury and Tech.

We help our clients to solve their most difficult problems around Cloud Computing & DevOps, Data Platform, IT Security by having a holistic approach of their environment and building often complex but always relevant solutions to help them accelerate their business.

As a Data Platform Enablement Engineer, you will be acting as the vital link between feature teams and platform engineers, you will champion the adoption and evolution of our data platform by delivering hands‑on technical support, sharing best practices, and driving knowledge sharing initiatives.

Through proactive engagement, direct support, and continuous feedback collection you will foster a collaborative, innovative, and high‑impact environment—ensuring our platform continually adapts and delivers maximum value to its users.

Technological Environment

AWS: S3, EMR, Glue, Athena, Lake Formation, Cloud Formation, CDK, Lambda, Fargate

DevOps: Jenkins, SonarQube, Conda

Location: Based in Paris, 3 days onsite presence is required

Key Responsibilities

Make sure technical debt is identified, understood and managed through action plans and participate to their underlying tasks. Provide tooling to help manage this debt (testing, automation, AI agents, …)

Promote the adoption of the data platform by daily usage, delivering its value to existing users.

Assess current team level on Data Platform tools and practices and improve it with training, exercises and solutioning real world problems.

Advocate for data engineers and data scientists within the company, ensuring their needs and challenges are understood and addressed.

Skills Needed for the Role

Proficient in Python development and crafting scalable, high‑quality applications.

Experience with data processing frameworks such as Pandas or Spark. Hands‑on experience developing and maintaining end‑to‑end data pipelines.

Deep expertise in AWS, complemented by certifications or equivalent experience.

Experience in Infra‑as‑Code framework (ideally AWS CDK in Python).

Knowledge of DevOps practices and CI/CD pipelines to improve deployment processes.

Excellent communication and presentation skills, capable of explaining complex technical concepts to diverse audiences.

Passionate about engaging with developer communities and creating a positive impact.

Good proficiency in both English and French.

Application Process

An introductory call with the recruiter.

A technical interview with one of our Sr. Engineer Consultants.

An interview with the client.

Seniority Level Mid‑Senior level

Employment Type Contract

Job Function Engineering and Consulting

Industries Funds and Trusts; IT Services and IT Consulting

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