Data Engineer at Vontier

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

17 Jul, 26

Salary

0.0

Posted On

18 Apr, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, ETL/ELT, Apache Airflow, Cloud Platforms, Healthcare Data Standards, SQL, NoSQL, DataOps, CI/CD, Data Quality, Machine Learning, Data Infrastructure, HIPAA, Python, Data Modeling, Cloud Architecture

Industry

electrical;Appliances;and Electronics Manufacturing

Description

Job Summary: The Data Engineer designs, builds, and maintains scalable data pipelines and infrastructure to support AI-driven healthcare SaaS applications. This role ensures data integrity, security, and compliance while enabling advanced analytics and machine learning capabilities. The Data Engineer collaborates with cross-functional teams to deliver reliable data solutions that improve clinical and operational outcomes within secure, scalable, and compliant cloud-native environments. Key Responsibilities: 1. Data Pipeline Development & ETL/ELT Engineering * Design, build, and optimize robust ETL/ELT pipelines using tools such as Apache Airflow, Talend, Informatica, or dbt. * Transform raw healthcare data into structured formats for analytics and AI/ML model consumption. * Ensure data quality, integrity, and reliability throughout the pipeline lifecycle. 2. Cloud-Native Architecture & AI Technologies * Develop and maintain data infrastructure on cloud platforms (AWS, Azure, GCP). * Engineer scalable data solutions using Fabric. * Support real-time and batch data processing for advanced analytics and machine learning workflows. 3. Healthcare Data Standards & Compliance * Ensure solutions adhere to healthcare data standards (HIPAA, HL7, FHIR) and regulations (GDPR, CCPA). * Implement secure and compliant data handling practices across systems. * Stay current with healthcare regulations and data privacy requirements. 4. AI/ML Workflow Support * Prepare and manage data for AI/ML model development, deployment, and monitoring. * Support feature engineering, model monitoring, and real-time data streaming for AI/ML initiatives. * Collaborate with AI/ML engineers and data scientists to enable seamless integration of models into production. 5. Database Management & Optimization * Manage and optimize relational and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra, DynamoDB). * Write complex SQL queries, perform joins, and tune database performance. * Ensure scalability, reliability, and security of data storage solutions. 6. DataOps, Automation & Continuous Improvement * Implement DataOps practices and automation for data workflows using Airflow, dbt, and CI/CD pipelines. * Support streaming and real-time data solutions with Apache Kafka, Spark Streaming, or Flink. * Commit to continuous improvement and staying current with industry trends and best practices. 7. Collaboration & Communication * Work closely with product, engineering, clinical, and compliance teams to deliver integrated data solutions. * Share knowledge and mentor team members on data engineering concepts and tools. * Communicate effectively to ensure alignment with business and technical goals. Required Qualifications: Education & Experience Guidelines * Bachelor’s Degree in computer science, data science, or other relevant field. * 5-8 years of relevant work experience * Experience with cloud platforms, data pipeline tools, and healthcare data standards * Exposure to AI/ML workflows and real-time analytics is a plus * Occasional travel may be required. Other Preferred Knowledge, Skills, Abilities or Certifications: * Cloud Certifications: AWS Data Analytics, Azure Data Engineer, Google Cloud Data Engineer * Streaming & Real-Time Data: Apache Kafka, Spark Streaming, Flink * DataOps & Automation: Airflow, dbt, CI/CD for data workflows * Security & Compliance: HIPAA, GDPR, CCPA, data encryption * Advanced Databases: PostgreSQL, MongoDB, Cassandra, DynamoDB * AI/ML Support: Feature engineering, model monitoring, ML pipeline integration Fortive 9 Behaviors by Level: Influencing & Mentoring Customer Obsessed: Champions a customer-focusedculture by anticipating evolving needs and shaping solutions that deliver long-term value. Strategic: Drives organizational impact by using data to derive insights that inform near-term and mid-range goals Innovation for Impact: Influences innovation through demonstrating bold thinking and experimentation in own work and coaching others to do the same. Inspiring: Demonstrates purpose-driven impact through expertise and collaboration. Builds Extraordinary Teams: Drives impact through collaboration and influence by fostering trust, sharing expertise, and aligning efforts across teams. Courageous: Influences and leads by example through action and integrity—moves quickly toward goals, tackles challenges head-on, and encourages open sharing of ideas without fear. Delivers Results: Leads complex initiatives to successful completion with high standards, precision, and urgency. Adaptable: Applies rigor and stays true to process while fostering adaptability within the team. Lead with FBS: Embraces FBS and models lean principles by mentoring peers and influencing teams, and going to Gemba for first-hand insights.

Responsibilities

The Data Engineer will design, build, and maintain scalable data pipelines and infrastructure to support AI-driven healthcare SaaS applications. They will collaborate with cross-functional teams to ensure data integrity, security, and compliance while enabling advanced analytics and machine learning capabilities.