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Deutsche Telekom Digital Labs

Posted 27 Aug 2026

Director - Data Engineering

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Employment
Full time
Team
Software Engineering
Posted
27 Aug 2026

About the role

We are looking for a Director - Data Engineering to lead the data engineering strategy, architecture, and execution for a large-scale consumer-facing platform. The ideal candidate will have strong experience building and scaling modern data platforms that power customer-facing products, personalisation, analytics, experimentation, recommendations, and business intelligence. This role requires a strong combination of technical depth, data architecture expertise, engineering leadership, and stakeholder management, with hands-on experience across GCP-based modern data ecosystems.


Responsibilities:

  • Define and drive the enterprise data engineering strategy and roadmap aligned with business and product objectives.
  • Architect and scale highly available, secure, and cost-efficient GCP data platforms capable of handling large-scale consumer data.
  • Lead data engineering teams responsible for batch and real-time data pipelines, data platforms, data products, and analytics infrastructure.
  • Design and implement modern data architectures across data lake, data warehouse, lakehouse, streaming, and analytical platforms.
  • Drive adoption of GCP services such as BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Storage, Composer, Cloud Functions and related services.
  • Build robust data pipelines integrating data from customer, product, transaction, marketing, operational, and third-party systems.
  • Partner closely with Product, Engineering, Analytics, Data Science, ML, Marketing, and Business teams to build data products that directly impact the customer journey.
  • Enable data capabilities for personalisation, recommendation, search, customer segmentation, experimentation, customer analytics, and real-time decisioning.
  • Establish strong standards around data quality, governance, lineage, security, privacy, observability, and reliability.
  • Drive modernisation of legacy data platforms and migration toward scalable cloud-native architectures.
  • Establish engineering best practices around CI/CD, automated testing, monitoring, performance optimisation, and infrastructure automation.
  • Optimise data platform performance and cloud costs at scale.
  • Mentor and develop senior engineering leaders and build a high-performing data engineering organisation.
  • Influence senior leadership and stakeholders on data strategy, architecture, investment priorities, and technology decisions.


Requirements:

  • 14-18 years of overall experience in Data Engineering / Data Platforms / Data Architecture.
  • Strong experience leading large-scale data engineering teams and organisations.
  • Proven experience building and scaling consumer-facing B2C/D2C platforms with significant transaction, customer, or behavioural data volumes.
  • Strong hands-on expertise with Google Cloud Platform (GCP).
  • Deep experience with BigQuery, Dataflow, Pub/Sub, Cloud Storage, Dataproc, Composer/Airflow or equivalent GCP data services.
  • Strong understanding of data lake, data warehouse, lakehouse and modern data platform architectures.
  • Experience with both batch and real-time/streaming data pipelines.
  • Strong programming experience in Python, Java, or Scala.
  • Strong knowledge of SQL, distributed systems, data modelling, ETL/ELT and data processing frameworks.
  • Experience designing highly scalable and reliable data systems handling millions of customers / high-volume consumer data.
  • Strong understanding of data governance, security, privacy, data quality, lineage and observability.
  • Excellent stakeholder management skills with the ability to work with C-level executives, Product, Engineering, Data Science and Business leadership.


Strongly Preferred:

  • Experience in high-scale consumer businesses such as E-commerce, Marketplace, FinTech, Travel, Mobility, FoodTech, Retail, Media or Internet platforms.
  • Experience supporting personalisation, recommendations, search, customer 360 experimentation and real-time analytics.
  • Experience with Kafka, Spark, Databricks, Snowflake or other modern data technologies.
  • Exposure to ML/AI data platforms and MLOps.
  • Experience driving 01 data platform initiatives as well as large-scale platform modernisation.
  • Experience managing multiple engineering managers / senior technical leaders.


Leadership Expectations:

  • Strong people leadership and organisational building capabilities.
  • Ability to balance strategic thinking with technical depth.
  • Strong ownership mindset with a bias toward execution.
  • Excellent communication and influencing skills.
  • Ability to simplify complex data architecture and communicate effectively with business and technology leadership.
  • Strong focus on building scalable, reliable, secure and business-impactful data platforms.
  • B. Tech / BE / MCA / equivalent technical qualification from a reputed institution preferred.


What Success Looks Like:

  • A scalable and future-ready GCP data platform supporting the organisation's consumer ecosystem.
  • Faster and more reliable access to high-quality data across Product, Engineering, Analytics and Business teams.
  • Stronger real-time data capabilities for personalisation, recommendations and customer experiences.
  • Improved data quality, governance, reliability and platform cost efficiency.
  • A high-performing data engineering organisation with strong technical leadership and execution capabilities.

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