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Posted 2w ago

Data Engineer

@ Fortive
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Bengaluru, Karnataka, India
HybridFull Time
Responsibilities:Designing pipelines, Transforming data, Ensuring governance
Requirements Summary:Bachelor’s degree in computer science or data science; 5-8 years of experience; cloud platforms and data pipeline tools; healthcare data standards knowledge; AI/ML workflow exposure; occasional travel.
Technical Tools Mentioned:Airflow, Talend, Informatica, dbt, Apache Kafka, Spark Streaming, Flink, AWS, Azure, GCP, PostgreSQL, MongoDB, Cassandra, DynamoDB
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Job 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.