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Open nowPosted 227 days ago

Senior Data Engineer

Indicium AI34 open roles

Where
Lisbon
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Your applicationOpen nowSenior Data EngineerIndicium AI · Lisbon

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Indicium AI's own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. Indicium AI postings stay open a median of 28 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 227 days ago

Indicium AI median: 28 days open

The posting

About Indicium AI

Indicium AI is trusted by the world's leading enterprises to deliver AI into production at scale. We are a global AI-native consultancy with proven experience across Financial Services, Energy & Utilities, Healthcare & Life Sciences, Retail & CPG, and Manufacturing. From strategy, to build, to business outcomes, we unlock value from AI with unmatched clarity, speed, and capability.

Powered by 600+ AI experts serving 50+ enterprise clients from 5 global locations, we work side-by-side with top partners - including Anthropic, Databricks, AWS, OpenAI, and Microsoft - to deliver modern AI with speed and measurable impact.

ABOUT THE ROLE

As a Senior Data Engineer at Indicium AI, you will serve as a technical authority within client engagements — leading architectural decisions, owning the delivery of complex data platforms, and shaping engineering standards across the engagement. This role requires someone who combines expert-level engineering with the communication skills to influence stakeholders, mentor colleagues, and drive the highest standards of data platform delivery.

KEY RESPONSIBILITIES

Architecture & Technical Leadership

  • Lead the end-to-end design and delivery of scalable, production-grade data architectures including Data Warehouses, Data Lakes, and Lakehouses.
  • Define data engineering standards, patterns, and guardrails used across the team and client engagements.
  • Exercise full technical autonomy — propose, challenge, and refine architectural solutions with clients and internally.

Advanced Pipeline Engineering

  • Architect, build, and maintain mission-critical ELT pipelines.
  • Optimise complex data workflows for performance, cost efficiency, and long-term maintainability.

Infrastructure & Platform Engineering

  • Own data infrastructure provisioning and lifecycle management via Infrastructure as Code (Terraform), ensuring scalability, security, and reliability at enterprise scale.
  • Lead cloud architecture decisions across AWS and/or Azure, aligning platform choices to client strategy and commercial constraints.

Governance, Security & Reliability

  • Establish and enforce data governance frameworks — access policies, data quality standards, lineage, and observability — in complex, regulated environments.
  • Define and own SLA commitments for critical data pipelines, leading incident response and continuous improvement efforts.

Client & Stakeholder Engagement

  • Act as a trusted technical advisor to senior client stakeholders, translating complex engineering decisions into clear business implications.
  • Contribute to pre-sales and scoping conversations, helping shape technically sound and commercially viable engagements.

Mentorship & Team Development

  • Mentor junior and mid-level engineers, fostering a culture of engineering excellence, curiosity, and continuous learning.
  • Champion DevOps and DataOps practices — CI/CD, testing, observability, and documentation — as non-negotiable standards.
  • Drive research into emerging technologies and tools, translating findings into practical recommendations for the practice.

REQUIREMENTS

At Indicium AI we believe in personal growth and professional development, and are convinced that the perfect candidate is one that continuously learns. Therefore, these requirements are an || and not an &&

Technical

  • Programming: 5+ years of professional experience building production data systems, primarily in Python. Proficiency in at least one additional language (Scala, Java, etc.).
  • SQL: Expert-level SQL — schema design, complex query optimisation, and deep platform-specific knowledge (Snowflake, Redshift, etc.).
  • dbt: Advanced dbt expertise. dbt Developer or dbt Architect certification is highly desirable (preference but not mandatory).
  • Big Data: Deep experience with orchestration and transformation tooling like Spark, Presto, or Airflow — capable of leading complex aggregation and transformation logic at scale.
  • IaC: Advanced Terraform experience — modules, remote state, workspace management, and cloud-specific provider expertise.
  • Cloud Architecture: Advanced, multi-cloud experience (AWS, Azure) with professional or specialty-level certification on at least one platform.
  • Version Control & CI/CD: Advanced Git workflows with hands-on ownership of CI/CD pipelines for data platform delivery.

Soft Skills & Language

  • Strong written and spoken English.
  • Strong consultative instinct — you listen carefully, ask the right questions, and tailor solutions to client context.
  • Resilient and decisive under ambiguity; comfortable leading delivery with incomplete information in fast-moving engagements.

Benefits

  • Holiday Entitlement - 25 days holiday plus bank holidays
  • Learning & Development: 1.500€ training budget + 5 training days
  • Company Bonus - Discretionary company and personal bonus paid quarterly
  • Pension Scheme
  • Choose Your Kit - Select from a range of laptops and accessories
  • Social Events: meeting - Ups, Squad events, Summer/ Christmas events, etc.
  • And many others.
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