• Design, build, and maintain end‑to‑end data pipelines and integrations to support Medicine & Analytics use cases (batch and event‑driven patterns where relevant). • Develop, operate, and optimize integrations using SnapLogic and AWS services such as S3, AWS Lambda, and AWS Glue to ensure robust ingestion, transformation, and orchestration. • Implement and maintain analytics‑ready data models in Snowflake, ensuring performance, scalability, and cost‑efficient design. • Build transformation logic and analytics layers using dbt, including modular modeling, testing, documentation, and deployment best practices. • Contribute to and enforce data governance standards by leveraging tools such as Collibra, ensuring metadata quality, lineage, ownership, and consistent definitions. • Partner with Data Quality stakeholders to implement and monitor quality controls using Attaccama, including rules, profiling, exception handling, and remediation workflows. • Support data lifecycle processes and operationalization of data products using Innovator (as applicable in the ecosystem) to align delivery with platform and product standards. • Proactively identify opportunities to simplify architecture, automate repetitive work, and reduce operational effort (observability, alerting, self‑healing patterns). • Ensure all solutions follow security, privacy, and compliance expectations (e.g., regulated environment practices, audit readiness, access controls, data handling). • Collaborate closely with Product Owners, Data Scientists, Analysts, Architects, and business stakeholders to translate needs into reliable, reusable data assets. • Act as a role model for engineering excellence: version control, CI/CD, code reviews, documentation, and operational runbooks.

• Build, maintain, and run CI/CD pipelines and infrastructure-as-code for the Smile Digital Health platform and associated services. • Provision, configure, and operate cloud-based Spark clusters and distributed data processing environments, including hands-on work with orchestration tools such as Airflow, Databricks, or EMR. • Write, test, and maintain data pipelines on the same infrastructure you manage, from environment setup through to production monitoring. • Design and maintain scalable, secure infrastructure templates and deployment automation across AWS, Azure, GCP, or OCI environments. • Investigate and resolve data pipeline and integration issues, providing root-cause analysis and durable fixes. • Monitor running systems and pipelines, respond to incidents, tune performance, and manage cloud infrastructure costs. • Foster an Everything-as-Code culture and promote DataOps best practices across the team. • Assist developers and engineers with deployments and builds as needed.

Expertise in AWS Glue, Lamda, EMR Expertise in SQL Expertise in ETL/ELT At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus. Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself. We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.

Ascendis Pharma is a dynamic, fast-growing global biopharmaceutical company with locations in Denmark, Europe, and the United States. Today, we're advancing programs in Endocrinology Rare Disease and Oncology. Here at Ascendis, we pride ourselves on exceptional science, visionary leadership, and skilled and passionate colleagues. Guided by our core values of Patients, Science, and Passion, we use our TransCon® drug development platform to fulfill our mission of developing new and potentially best-in-class therapies to address unmet medical needs. Our culture fosters a place where skilled, adaptable, and highly resourceful professionals can truly make their mark. We offer a dynamic workplace for employees to grow and develop their skills. The Data Science Summer Intern will support the Global Biometrics department by contributing to R-based data analysis and reporting solutions used by clinical development teams. This role provides hands-on experience with exploratory analyses, surveillance-style reporting, and reproducible analytics in a collaborative and regulated research environment.  This internship is structured as a learning and development opportunity. The intern will receive mentorship from experienced data scientists and gain exposure to real-world clinical data science workflows, tools, and best practices.  Key Responsibilities  - Support the maintenance and enhancement of R Markdown reports and Shiny apps  - Contribute to clear and well-documented analytical deliverables (code comments, README files, and basic user documentation)  - Collaborate with cross-functional team members to understand analytical requirements and incorporate feedback  - Apply standard practices for reproducible research, version control, and organized project structure  Learning and Development Opportunities  - Practical experience using R and RStudio in an enterprise data science setting  - Exposure to reproducible reporting, structured analytical workflows, and version control practices  - Introduction to enterprise analytics, development, and AI-enabled productivity tools (e.g., Posit environment, Azure DevOps, Microsoft CoPilot)  - Insight into how data science supports clinical development and evidence-based decision-making  - Ongoing mentorship and guidance from senior data scientists within Global Biometrics