3 days ago

Senior Data Platform Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 21 hours agoStatus: Live

Job Summary

Build and evolve a secure, reliable data platform used across the company, including a Databricks-based lakehouse, Kafka-based ingestion, and data tooling like dlt. Enable AI-powered data workflows through connectors, MCP integrations, and workflow skills for humans and AI agents. Improve data trust with observability, monitoring, and quality frameworks, while stewarding infrastructure, governance, and developer experience using Terraform/Terragrunt and CI/CD.

Location: London

Workplace: Hybrid

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Seniority: Mid level

Key Responsibilities

•Build and evolve the data platform infrastructure, including the Databricks-based lakehouse, Kafka ingestion, and tooling like dlt.
•Enable AI-powered data workflows by developing connectors, interfaces, and integrations for humans and AI agents (including MCP connectors and workflow skills).
•Make data trustworthy at scale through observability, data quality frameworks, monitoring, and alerting.
•Steward infrastructure and developer experience using infrastructure-as-code (Terraform/Terragrunt), CI/CD, access management, security configurations, audit trails, and spend governance.

Pay and Benefits

Perks:Paid LeaveEquity

Key Requirements

•Hands-on experience building and operating cloud data infrastructure, including infrastructure-as-code (Terraform/Terragrunt), CI/CD for data workflows, and containers (Docker/Kubernetes).
•Strong production Python skills (primary language on the Data Platform).
•A reliability mindset: build for observability, write meaningful alerts, own systems in production, and improve after incidents.
•Platform-product mindset: treat engineers and data consumers as primary users, improve developer experience, and proactively reduce friction.
•Clear cross-functional communication and ability to incorporate feedback from data consumers to improve the platform.

Skills:ReliabilityOperational excellenceCross-functional communicationPlatform-product mindsetResponsibility

Tech Stack:PythonGoJavaTerraformTerragruntCI/CDDockerKubernetesDatabricksKafkaDltMCPWorkflow skillsIntegrationsApache Iceberg

Company Brief

DeepL

DeepL builds Language AI products (DeepL Translator, DeepL Write, APIs and enterprise solutions) that provide high-accuracy translations and writing assistance to businesses and individuals, focusing on privacy, security and enterprise deployment.

Industry: AI & Machine Learning

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series D

Headquarters: Cologne, Germany

Founded: 2017

Glassdoor: 3.5

Website LinkedIn Glassdoor

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DeepL

3 days ago

Senior Data Platform Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 21 hours agoStatus: Live

Job Summary

Location: London

Workplace: Hybrid

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Seniority: Mid level

Key Responsibilities

•Build and evolve the data platform infrastructure, including the Databricks-based lakehouse, Kafka ingestion, and tooling like dlt.
•Enable AI-powered data workflows by developing connectors, interfaces, and integrations for humans and AI agents (including MCP connectors and workflow skills).
•Make data trustworthy at scale through observability, data quality frameworks, monitoring, and alerting.
•Steward infrastructure and developer experience using infrastructure-as-code (Terraform/Terragrunt), CI/CD, access management, security configurations, audit trails, and spend governance.

Pay and Benefits

Perks:Paid LeaveEquity

Key Requirements

•Hands-on experience building and operating cloud data infrastructure, including infrastructure-as-code (Terraform/Terragrunt), CI/CD for data workflows, and containers (Docker/Kubernetes).
•Strong production Python skills (primary language on the Data Platform).
•A reliability mindset: build for observability, write meaningful alerts, own systems in production, and improve after incidents.
•Platform-product mindset: treat engineers and data consumers as primary users, improve developer experience, and proactively reduce friction.
•Clear cross-functional communication and ability to incorporate feedback from data consumers to improve the platform.

Skills:ReliabilityOperational excellenceCross-functional communicationPlatform-product mindsetResponsibility

Tech Stack:PythonGoJavaTerraformTerragruntCI/CDDockerKubernetesDatabricksKafkaDltMCPWorkflow skillsIntegrationsApache Iceberg

Company Brief

DeepL

Industry: AI & Machine Learning

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series D

Headquarters: Cologne, Germany

Founded: 2017

Glassdoor: 3.5

Website LinkedIn Glassdoor