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Salary
≈ $30k – $80k per year (Estimated)
Location
In office (Gurgaon)
Seniority
Principal · 12+ years exp

First seen by Alion on Aug 24, 2026.

Overview
Company
Impact
Profile match
Bupa is a global healthcare company that delivers a broad range of health services, including aged care and retirement, hospitals, health insurance, and community wellbeing initiatives to over 60 million customers.

We are looking for an experienced Engineering Manager - Data (GCP) to lead our data engineering function, driving the design, development, and scaling of our cloud-native data platform on Google Cloud Platform (GCP). This role combines strong technical depth in data architecture with proven people leadership and is ideal for someone who has grown from a hands-on data engineer/architect into a leader who can build and scale high-performing teams while staying close to technical decision-making.

The core responsibilities for the job include the following:

Technical Leadership:

  • Own the architecture, design, and roadmap of the data platform built on GCP (BigQuery, Dataflow, Pub/Sub, Cloud Composer, Dataproc, Cloud Storage, etc. ).
  • Drive best practices for data pipeline design, data modeling, data quality, and data governance.
  • Evaluate and introduce new tools, frameworks, and architectural patterns to improve scalability, reliability, and cost efficiency.
  • Ensure platform security, compliance, and adherence to data privacy standards.
  • Participate in critical design reviews, architecture decisions, and troubleshooting of complex production issues.

People and Team Management:

  • Lead, mentor, and grow a team of data engineers, senior engineers, and tech leads (team size: 10-25+).
  • Own hiring, performance management, career development, and succession planning for the team.
  • Foster a culture of engineering excellence, ownership, and continuous learning.
  • Manage team structure, capacity planning, and workload distribution across projects.

Program and Stakeholder Management:

  • Partner with product, analytics, data science, and business stakeholders to translate requirements into scalable data solutions.
  • Own delivery timelines, sprint planning, and execution using Agile/Scrum methodologies.
  • Manage budgets, cloud cost optimization, and vendor/tool evaluations.
  • Report on team KPIs, platform health, and project status to senior leadership.

Strategy:

  • Define and execute the long-term data engineering strategy aligned with business goals
  • Drive migration/modernization initiatives (e. g., on-prem to GCP, legacy pipeline re-architecture)
  • Contribute to org-level engineering initiatives, standards, and best practices

Requirements:

  • Bachelor's or master's degree in computer science, engineering, or a related field.
  • 12-16 years of overall experience in software/data engineering, with at least 3-5 years in a people management role (managing engineers/tech leads).
  • Strong hands-on background in data engineering and architecture, with deep expertise in Google Cloud Platform (GCP) BigQuery, Dataflow, Pub/Sub, Cloud Composer (Airflow), Dataproc, Cloud Storage, and IAM.
  • Proven experience building and scaling large-scale batch and streaming data pipelines.
  • Strong understanding of data modeling, data warehousing, ETL/ELT design, and distributed systems.
  • Proficiency in SQL and at least one programming language (Python/Java/Scala).
  • Experience with orchestration tools (Airflow/Cloud Composer), CI/CD pipelines, and Infrastructure as Code (Terraform preferred).
  • Solid understanding of data governance, security, and compliance frameworks (GDPR, SOC2 etc. ).
  • Demonstrated experience managing stakeholders across cross-functional teams (Product, Analytics, Data Science).
  • Strong communication, planning, and organizational skills.
  • Experience with Agile/Scrum delivery frameworks.

Good to Have:

  • GCP certification (Professional Data Engineer / Professional Cloud Architect).
  • Experience with multi-cloud or hybrid-cloud data environments.
  • Exposure to ML/AI platform integration (Vertex AI) and MLOps.
  • Prior experience in a product-based or high-growth startup environment.
  • Experience with data mesh or modern data stack architectures.
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