Engineering Manager

Deutsche Telekom Digital Labs · Mobile Networks · IT Consulting & Digital Transformation · Python · ETL/ELT · 6 days ago

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Salary

≈ $32k – $83k per year (Estimated)

Location

In office (Gurgaon)

Seniority

Staff · 10+ years exp

First seen by Alion on Oct 23, 2026.

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Deutsche Telekom Digital Labs

Deutsche Telekom Digital Labs is the Indian engineering centre of the German telecommunications group Deutsche Telekom, established in Gurgaon in 2018. Its teams build the digital products the group ships across its European markets, including the customer applications used by mobile and broadband subscribers, the commerce and ordering systems behind them, television and streaming clients, and the platform and data infrastructure shared between national operating companies. The centre works as a product organisation rather than an outsourcing vendor, owning services end to end and releasing them into several European markets at once.

dtdl.in · HQ: Gurgaon, India · Mobile Networks · IT Consulting & Digital Transformation · Est. 2018

Tech stack of Deutsche Telekom Digital Labs

We are looking for an Engineering Manager (Data Engineering) to lead the design and delivery of scalable data platforms and pipelines. The ideal candidate should have strong expertise in Python, PySpark, Spark, and AWS or GCP, along with experience managing high-performing engineering teams.

Responsibilities:

Lead and mentor data engineering teams to deliver scalable and reliable data solutions.
Design and develop data pipelines using Python, PySpark, and Spark.
Build and optimise data platforms on AWS or GCP.
Collaborate with Product, Analytics, and Business teams to deliver data-driven solutions.
Drive architecture, code quality, performance optimisation, and engineering best practices.
Ensure scalable, secure, and high-performance data processing systems.

Requirements:

10.5-13.5 years of experience in data engineering.
Strong expertise in Python, PySpark, Spark, and AWS or GCP.
Experience building large-scale ETL pipelines and data processing frameworks.
Good understanding of distributed systems, data lakes, and cloud-native architectures.
Proven experience leading engineering teams in a product-based environment.
Strong communication, leadership, and problem-solving skills.

Skills

PySpark, Python, Spark

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