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Data Engineer

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Hybrid

Data Engineer

Pharmanovia

Data Engineer

Skills

SQL QueriesData EngineeringPythonDatabricksData AnalysisAWSProcess ImprovementSupply Chain

4 days ago

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Important information


Contract type:

Permanent

Location:

Mumbai, Maharashtra, India

Work mode:

Hybrid

Published on:

16 October 2026

What they need


Data Engineer - India - Mumbai or Vadodara - Hybrid - 3D WFO-2D WFH

About the Company

Pharmanovia is a global speciality pharmaceutical company focused on innovative speciality medicines and trusted, established brands. Pharmanovia combines scientific, medical, regulatory, market access, supply chain and commercial expertise to bring medicines to patients. Together, they reflect a business built to meet patient needs today while helping shape better outcomes for tomorrow.

About the Role

The Data Engineer will play a critical role in building, maintaining, and evolving Pharmanovia’s cloud data platform. This role sits at the heart of the organisation’s data capability, ensuring that data is reliable, well-governed, and scalable to support commercial decision-making, supply chain planning, and operational execution across the business.

The Data Engineer will be responsible for designing and implementing robust batch data pipelines, managing data quality and governance within the lakehouse, and maintaining key internal data tools. They will work closely with business stakeholders to identify manual or inefficient processes and replace them with automated, data-driven solutions that remove bottlenecks and improve operational efficiency.

Responsibilities

Data Pipeline Engineering & Platform Ownership:

  • Design, build, and maintain scalable, reliable batch data pipelines using Databricks, Python, SQL, and AWS.
  • Own and support hundreds of event-driven data pipelines, many of which run daily and underpin critical business processes.
  • Take end-to-end responsibility for data pipelines, from ingestion through transformation to delivery.
  • Ensure pipelines are robust, well-documented, and fit for purpose in a production environment.

Data Governance, Quality & Access Control:

  • Define, implement, and uphold data governance standards, including naming conventions, schema evolution, and access control.
  • Actively manage data quality within the lakehouse, implementing validation checks, monitoring, and alerting.
  • Investigate data quality issues and failures, identifying root causes and implementing durable fixes.
  • Maintain high standards for data reliability, recognising that trust in data is critical to business success.

Automation & Process Improvement:

  • Partner with stakeholders across the business to identify manual, error-prone, or inefficient processes.
  • Design and deliver automated, data-driven solutions that remove operational bottlenecks.
  • Translate business problems into pragmatic engineering solutions that balance speed, robustness, and scalability.
  • Take ownership of automation initiatives from initial concept through to production deployment, as well as ongoing maintenance/support.

Internal Tools & Systems:

  • Maintain and enhance internal data tools and ingestion systems, including in-house solutions such as Email Muncher.
  • Ensure internal tooling remains reliable, secure, and aligned with platform standards and governance principles.
  • Contribute to the evolution of shared engineering patterns, frameworks, and reusable components.

Stakeholder Engagement & Collaboration:

  • Engage directly with stakeholders across commercial, supply chain, finance, and leadership teams to understand requirements and priorities.
  • Communicate technical concepts clearly to non-technical audiences, focusing on business impact and outcomes.
  • Act as a trusted technical partner, balancing engineering best practices with real-world business needs.

Self-Directed Problem Solving:

  • Proactively identify issues and opportunities within the data platform and wider business processes.
  • Take initiative to design and implement solutions without waiting for detailed instruction.
  • Maintain high standards and persist in finding the right answers, even when challenges arise.

Qualifications

Relevant Graduate degree (BCA/B.Tech/B.Sc CS/Mathematics, Business, or any related field).

Required Skills

  • 3- 5 years of experience in a commercial data engineering role or similar role
  • Pharmaceutical or healthcare industry experience.
  • Experience working in fast-paced, PE-backed or high-growth environments.
  • Experience with S&OP or supply chain analytics.
  • Strong Python programming skills.
  • Strong SQL skills for data transformation and validation.
  • Experience with Databricks or similar cloud data platforms.
  • Familiarity with AWS cloud services.
  • Experience using Git and DevOps-style workflows.
  • Experience implementing data quality monitoring and alerting.
  • Experience designing and maintaining production data pipelines.
  • Experience working directly with business stakeholders.
  • Proven ability to design and deliver solutions independently.
  • Experience maintaining data platforms critical to business operations.
  • Understanding of data governance principles (access control, schema management, naming standards).
  • Understanding of batch data processing at scale.
  • Understanding of Agile/DevOps working methodologies.
  • Exceptional drive and initiative – proactively identifies and solves problems. A self-starter who thrives working autonomously.
  • Strong stakeholder management skills with confidence engaging at senior levels.
  • Excellent communication skills, able to explain technical concepts clearly.
  • Collaborative team player who works effectively across functions with high attention to detail and commitment to data quality.
  • Results-oriented with a track record of delivering solutions end-to-end.

Pay range and compensation package

We offer a competitive salary plus a bonus and rewards package, including holidays, employee recognition awards, social events, a pension scheme, and hybrid working.

Equal Opportunity Statement

Pharmanovia is an equal-opportunity employer. Pharmanovia does not unlawfully discriminate against employees or applicants for employment based on an individual’s race, colour, religion, creed, sex, sexual orientation, gender identity or expression, national origin, genetic information, age, disability, marital status or any other status protected by applicable law. This policy applies to all terms, conditions, and privileges of employment, including recruitment, hiring, placement, compensation, promotion, discipline, and termination. Pharmanovia will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law.

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