Data - Senior Engineer

Job Description Why Join Iris Are you ready to do the best work of your career at one ofIndia's Top 25 Best Workplaces in IT industry Do you want to grow in an award-winning culture thattruly values your talent and ambitions Join Iris Software - one of thefastest-growing IT services companies- whereyou own and shape your success story. About Us At Iris Software, our vision is to be our client's most trusted technology partner, and the first choice for the industry's top professionals to realize their full potential. With over 4,300 associates across India, U.S.A, and Canada, we help our enterprise clients thrive with technology-enabled transformation across financial services, healthcare, transportation & logistics, and professional services. Our work covers complex, mission-critical applications with the latest technologies, such as high-value complex Application & Product Engineering, Data & Analytics, Cloud, DevOps, Data & MLOps, Quality Engineering, and Business Automation. Working with Us At Iris, every role is more than a job - it's a launchpad for growth. Our Employee Value Proposition, Build Your Future. Own Your Journey.reflects our belief that people thrive when they have ownership of their career and the right opportunities to shape it. We foster a culture where your potential is valued, your voice matters, and your work creates real impact. With cutting-edge projects, personalized career development, continuous learning and mentorship, we support you to grow and become your best - both personally and professionally. Curious what it's like to work at Iris Head to this video for an inside look at the people, the passion, and the possibilities. Watch it . Job Description The Principal Data Engineer will be a senior individual contributor responsible for designing, building, and optimizing advanced data solutions that power enterprise-wide analytics, AI/ML, and data-driven decision-making. Reporting directly to the Senior Director of Data Platforms, this role will serve as a technical expert and thought partner in scaling modern data architectures, enabling AI orchestration, and delivering robust, secure, and compliant data products. This position is highly hands-on, requiring expertise in data engineering, Databricks, Python, AI/ML platforms, and orchestration frameworks. The Principal Engineer will work across functional teams to design and implement high-performance pipelines, ensure platform reliability, and set technical standards for the organization's data engineering practices. Job Duties & Responsibilities - Design & Build Data Systems: Architect and implement scalable data pipelines, lakehouse/lake/warehouse environments, APIs, and orchestration workflows to support analytics, AI/ML, and business intelligence. - Enable AI & ML at Scale: Partner with Data Science and AI teams to productionize ML models, automate workflows, and enable AI orchestration frameworks (e.g., MLflow, Airflow, Databricks workflows). - Technical Leadership: Act as a hands-on subject matter expert in Databricks, Python, Spark, and related technologies-driving adoption of best practices and mentoring other engineers. - Optimize Performance: Ensure data pipelines and platforms are highly available, observable, and performant at scale through monitoring, automation, and continuous improvement. - Ensure Compliance & Security: Build solutions that adhere to data governance, privacy, and regulatory frameworks (HIPAA, SOC 2, GCP, GDPR) within clinical research, life sciences, and healthcare contexts. - Collaborate Across Functions: Work closely with platform engineering, analytics, product management, and compliance teams to deliver aligned solutions that meet enterprise needs. - Advance Modern Architectures: Contribute to evolving data platform strategies, including event-driven architectures, data mesh concepts, and lakehouse adoption. Location This role is open to candidates working in the United States (remote or hybrid). Basic Qualifications - Bachelor's degree in Computer Science, Engineering, Data Science, or equivalent practical experience. - 8+ years of data engineering experience in designing, implementing, and optimizing large-scale data systems. - Strong proficiency in Python, with production-level experience in building reusable, scalable data pipelines. - Hands-on expertise with Databricks (Delta Lake, Spark, MLflow), and modern orchestration frameworks (Airflow, Prefect, Dagster, etc.). - Proven track record of deploying and supporting AI/ML pipelines in production environments. - Experience with cloud platforms (AWS, Azure, or GCP) for building secure and scalable data solutions. - Familiarity with regulatory compliance and data governance standards in healthcare or life sciences. Preferred Qualifications - Experience with event-driven systems (Kafka, Kinesis) and real-time data architectures. - Strong background in data modeling, lakehouse/lake/warehouse design, and query optimization. - Exposure to AI orchestration platforms and generative AI use cases. - Contributions to open-source projects or published work in data engineering/ML. - Agile development experience, including CI/CD, automated testing, and DevOps practices. Mandatory Competencies Development Tools and Management - Development Tools and Management - CI/CD Tech - Agile Methodology Data Science and Machine Learning - Data Science and Machine Learning - Gen AI Data Science and Machine Learning - Data Science and Machine Learning - AI/ML Big Data - Big Data - SPARK DevOps/Configuration Mgmt - Cloud Platforms - AWS DevOps/Configuration Mgmt - Cloud Platforms - GCP Cloud - Azure - Azure Data Factory (ADF), Azure Databricks, Azure Data Lake Storage, Event Hubs, HDInsight Beh - Communication and collaboration Perks and Benefits for Irisians Iris provides world-class benefits for a personalized employee experience. These benefits are designed to support financial, health and well-being needs of Irisians for a holistic professional and personal growth. Click to view the benefits.