Principal Data Engineer

ANSR is hiring for one of its clients.

About ANSR MedTech:

Who We Are:

ANSR MedTech Capability Center is a new global innovation hub being established in India for a Fortune 100 Fastest-Growing Company in the MedTech sector. Built in partnership with ANSR, the center draws on ANSR's proven experience in establishing and scaling high-performance Global Capability Centers (GCCs) for leading global enterprises.

ANSR MedTech center brings together world-class engineering, product, and technology talent to build next-generation healthcare platforms and solutions that power global operations.

Our Vision:

To build a next-generation MedTech capability center that powers global healthcare innovation. We envision:

• High-impact innovation hubs shaping global product and technology roadmaps
• Centers that go beyond support functions to drive core engineering and platform development
• Sustainable, scalable ecosystems that nurture world-class MedTech talent
• Capability centers that directly influence patient outcomes worldwide

At its core, the ANSR MedTech Capability Center is about enabling innovation that touches lives at scale.

Job Title: Principal Data Engineer

Location: Bengaluru, India

About the Role:

As a Principal Data Engineer, you'll work directly with the Data Engineering Leads and cross-functional teams on exciting, high-impact projects that shape the future of our products and data platform.

You'll be a key contributor organizing and helping the team with managing the backlog of work items building in collaboration with technical leads and stakeholders for our Databricks-based data infrastructure, ensuring it meets the rigorous standards of the medical device industry. This is a unique opportunity to blend technical expertise with product ownership, helping to drive innovation.

We offer a dynamic and collaborative work environment, where your attention to detail and passion for quality will directly influence product development, clinical insights, and operational efficiency. If you're looking for a role where your work truly matters—and where you'll grow alongside a team of talented engineers and healthcare professionals—this is the place for you.

• Building scalable data platforms and AI capabilities
• Engineering high-quality, production-ready data solutions
• Establishing standards, reliability, and long-term sustainability
• Growth defines what insights matter and how they are used
• CTO enables how those insights are delivered at scale
• Teams operate as one connected analytics organization, with clear ownership and shared outcomes

Responsibilities:

• Design, develop, and maintain scalable, resilient data architectures and pipelines for commercial data domains.
• Contribute to the design, implementation, and evolution of ANSR MedTech's enterprise data lake and warehouse architecture, leveraging Databricks and cloud-native services.
• Lead and participate in technical design discussions with engineers and stakeholders to align on architecture, standards, and implementation approach.
• Apply software /data engineering best practices—modular design, version control, testing, code reviews, and CI/CD—to data pipelines and platforms.
• Build and manage workflow orchestration for batch and event-driven pipelines using modern orchestration frameworks.
• Develop pipelines with automation-first principles, minimizing manual intervention and operational toil.
• Implement robust monitoring, alerting, retry, and failure-handling mechanisms to ensure production reliability.
• Perform proactive data quality checks, data validation, and remediation as part of automated pipelines.
• Collaborate with Analytics and Data Science teams to enable predictive, advanced, and AI-driven commercial analytics use cases.
• Develop and maintain data preprocessing and transformation frameworks reusable across analytical and AI workloads
• Partner with Cloud, IT, and Platform teams to optimize performance, scalability, cost, and security.

Cross-Functional & Global Collaboration:

• Work closely with U.S.-based data engineers, architects, and technical leads to align on:
• Architecture and design patterns
• Engineering standards and best practices
• Platform and operational consistency across regions
• Collaborate with cross-functional stakeholders across Commercial, Finance, IT, SAP, Quality, and Analytics teams to deliver end-to-end data solutions.
• Actively participate in global delivery and follow-the-sun collaboration models, ensuring smooth handoffs and shared ownership.

Preferred Qualifications:

• Experience supporting Commercial, Finance, or Order-to-Cash data domains.
• Exposure to AI/ML enablement, feature pipelines, or advanced analytics use cases.
• Familiarity with data governance, metadata management, or quality frameworks.
• Experience in regulated or highly governed data environments

Required Qualifications:

• Bachelor's or Master's degree in Engineering, Computer Science, or a related field, or equivalent practical experience.
• 10- 12 years of experience as a Data Engineer or ETL/ELT Platform Engineer in enterprise environments.
• Strong experience designing and building production-grade data pipelines using Databricks and Spark.
• Hands-on experience with ETL / ELT frameworks and cloud-based data platforms (e.g., Databricks, Azure Data Factory, cloud-native services).
• Strong background in data modeling, integration patterns, and enterprise data architecture.
• Experience working with SAP data sources, including SAP BI and SAP data modeling.
• Proficiency in Python and SQL, with a strong software engineering mindset.
• Experience with Data Governance tools such as Atlan, Alation, Collibra is a plus.
• HIPAA experience a plus

Skills/Competencies:

• Experience with workflow orchestration and managing complex data pipelines.
• Strong understanding of DataOps and DevOps principles, including CI/CD, automation, and observability.
• Ability to think end-to-end—from ingestion through consumption, operations, and support.
• Strong analytical and problem-solving skills, with high attention to detail and data quality.
• Ability to adapt to changing priorities and work effectively in ambiguous and evolving environments.
• Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders.
• Proven ability to collaborate effectively with globally distributed teams, including U.S.-based counterparts.