Overview
About Providence
Providence, one of the US’s largest not-for-profit healthcare systems, is committed to high quality, compassionate healthcare for all. Driven by the belief that health is a human right and the vision, ‘Health for a better world’, Providence and its 121,000 caregivers strive to provide everyone access to affordable quality care and services.
Providence has a network of 51 hospitals, 1,000+ care clinics, senior services, supportive housing, and other health and educational services in the US.
Providence India is bringing to fruition the transformational shift of the healthcare ecosystem to Health 2.0. The India center will have focused efforts around healthcare technology and innovation, and play a vital role in driving digital transformation of health systems for improved patient outcomes and experiences, caregiver efficiency, and running the business of Providence at scale.
Why Us?
- Best In-class Benefits
- Inclusive Leadership
- Reimagining Healthcare
- Competitive Pay
- Supportive Reporting Relation
- Define and implement scalable, efficient, and secure data architectures to meet organizational needs.
- Design & develop the architecture for data pipelines, data lakes, and data warehouses.
- Ensure alignment with business objectives and technology roadmaps. Design and build robust ETL/ELT pipelines to ingest, transform, and process large datasets from diverse sources.
- Designing and modelling Data lake solutions/data ingestion pipelines by collaborating with our customers and understanding requirements on digital transformation
- Implement real-time data streaming and batch processing solutions using modern tools and frameworks.
- Optimize pipelines for performance, scalability, and cost efficiency.
- Partner with data scientists to support AI/ML model development and deployment.
- Facilitate feature engineering, data preparation, and data versioning for AI/ML workflows.
- Implement MLOps practices, including model deployment, monitoring, and lifecycle management.
- Enforce data governance policies, including data quality, lineage, and security standards.
- Ensure compliance with data privacy regulations and organizational policies.
- Establish best practices for metadata management and data cataloging.
- Provide technical leadership and mentorship to data engineers and cross-functional teams.
- Advocate for engineering excellence and continuous improvement in data engineering practices.
- Drive innovation by exploring emerging technologies and methodologies.
- Analyze and optimize data systems for performance, reliability, and cost-effectiveness.
- Establish monitoring and alerting systems to ensure data pipeline health and integrity. Troubleshoot complex data engineering challenges and resolve bottlenecks.
- 8 – 12 years of experience in designing enterprise-scale data solutions, including cloud platforms with a strong focus on enterprise data strategy, architecture governance, and advanced analytics solutions
- Strong proficiency in building and maintaining large-scale data pipelines using tools like Apache Spark, Kafka, Airflow, or similar technologies.
- Expertise in SQL and programming languages such as Python, Scala, or Java.
- Hands-on experience with distributed data storage systems (e.g., Hadoop, Snowflake, Redshift, BigQuery). Deep understanding of cloud-based data platforms and services (AWS, Azure, GCP).
- Experience with cloud-native tools such as Azure Data Factory, or Google Cloud Dataflow.
- Proficient in designing data architectures that align with governance and compliance standards.
- Experience with data modeling, schema design, and data lineage.
- Proficiency in CI/CD pipelines and infrastructure-as-code tools like Terraform or CloudFormation.
- Knowledge of containerization and orchestration tools (Docker, Kubernetes).
- Strong ability to diagnose complex data engineering issues and implement effective solutions.
- Analytical mindset for optimizing performance and scalability.
- Familiarity with AI/ML workflows, including feature engineering, model training, and deployment. Knowledge in MLOps frameworks (MLflow, Kubeflow).
- Hands-on experience with deep learning models, NLP, or computer vision.
- Familiarity with advanced MLOps practices, such as automated retraining and continuous monitoring.
- In-depth knowledge of big data frameworks like Apache Hadoop, Hive
- Experience with graph databases or real-time analytics tools.
- Understanding of business processes and the ability to translate business needs into technical solutions.
- Experience working in domain-specific contexts such as healthcare, finance, or retail.
- Exploring and integrating cutting-edge technologies like generative AI, real-time analytics, or active metadata management.
Providence’s vision to create ‘Health for a Better World’ aids us to provide a fair and equitable workplace for all in our employment, whether temporary, part-time or full time, and to promote individuality and diversity of thought and background, and acknowledge its role in the organization’s success. This makes us committed towards equal employment opportunities, regardless of race, religion or belief, color, ancestry, disability, marital status, gender, sexual orientation, age, nationality, ethnic origin, pregnancy, or related needs, mental or sensory disability, HIV Status, or any other category protected by applicable law. In furtherance to our mission in building a more inclusive and equitable environment, we shall, from time to time, undertake programs to assist, uplift and empower underrepresented groups including but not limited to Women, PWD (Persons with Disabilities), LGTBQ+ (Lesbian, Gay, Transgender, Bisexual or Queer), Veterans and others. We strive to address all forms of discrimination or harassment and provide a safe and confidential process to report any misconduct.
Contact our Integrity hotline also, read our Code of Conduct.
- 1 - 7 Yrs
- Anywhere in India/Multiple Locations
- 5 - 12 Yrs
- Bangalore, Mumbai (All Areas), Hyderabad, Pune
- 12 - 16 Yrs
- India
- Bangalore, Karnataka, India
- Nasik, Maharashtra, India