Data Engineer at Weekday AI

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

09 Feb, 26

Salary

4000000.0

Posted On

11 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Azure Data Services, ETL Development, Databricks, FHIR Standards, SQL, Python, Scala, Data Modeling, Data Governance, CI/CD, DevOps, Data Quality, Problem Solving, Collaboration, Communication, Healthcare Data Integration

Industry

technology;Information and Internet

Description

This role is for one of the Weekday's clients Salary range: Rs 3000000 - Rs 4000000 (ie INR 30-40 LPA) Min Experience: 5 years Location: Bengaluru JobType: full-timeWe are seeking an experienced Data Engineer to design, build, and maintain robust data pipelines and architectures that power analytics, interoperability, and data-driven decision-making across our healthcare ecosystem. The ideal candidate will have a strong background in Azure data services, ETL development, Databricks, and hands-on experience with FHIR (Fast Healthcare Interoperability Resources) standards. This role requires a mix of technical proficiency, problem-solving ability, and a deep understanding of healthcare data integration. Key Responsibilities Data Pipeline Development: Design, develop, and optimize scalable ETL/ELT workflows to extract, transform, and load structured and unstructured healthcare data into Azure-based data platforms (e.g., Azure Data Lake, Azure Synapse, Databricks). FHIR Data Integration: Implement and manage FHIR-based data models and APIs for healthcare data interoperability. Ensure compliance with healthcare data standards and regulatory frameworks. Data Architecture & Modeling: Develop logical and physical data models to support data warehousing, reporting, and analytics needs. Ensure data accuracy, integrity, and security across all stages of the data lifecycle. Databricks Development: Build and manage scalable data processing solutions using Azure Databricks. Optimize performance of large-scale data transformations using PySpark, SQL, or Scala. Data Quality & Governance: Establish and maintain data quality frameworks, validation processes, and governance standards. Ensure consistent and compliant data handling across systems. Collaboration & Stakeholder Management: Partner with data scientists, analysts, architects, and business teams to deliver reliable and accessible data assets. Translate business requirements into technical solutions. Performance Optimization: Monitor, troubleshoot, and enhance data pipelines for performance, scalability, and cost efficiency in the Azure environment. Documentation & Best Practices: Maintain detailed documentation of architecture, data flows, and processes. Contribute to continuous improvement by implementing data engineering best practices and automation. Required Skills & Qualifications Education: Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Engineering, or a related field. Technical Skills: Strong expertise in Azure Data Services – Azure Data Factory, Azure Synapse, Azure Data Lake, and Azure SQL. Hands-on experience with Databricks for data processing, transformation, and analytics. Proven ability to design and maintain ETL/ELT pipelines using modern data engineering tools and frameworks. Proficiency in SQL, Python, or Scala for data manipulation and automation. Solid understanding of FHIR standards, data schemas, and API integration for healthcare data exchange. Experience with data modeling, metadata management, and data governance frameworks. Familiarity with CI/CD, Git, and DevOps practices in data engineering environments. Experience: 5–10 years of professional experience in data engineering, with at least 2 years of exposure to healthcare or interoperability projects leveraging FHIR. Soft Skills: Strong analytical and problem-solving abilities. Excellent communication and collaboration skills. Ability to work in a fast-paced, agile environment with cross-functional teams. Preferred Qualifications Experience with HL7, CDA, or other healthcare interoperability standards. Exposure to machine learning data pipelines or advanced analytics environments. Azure certifications (e.g., Azure Data Engineer Associate) are a plus.

Responsibilities

The Data Engineer will design, build, and maintain robust data pipelines and architectures to support analytics and data-driven decision-making in the healthcare ecosystem. Key responsibilities include developing ETL workflows, managing FHIR data integration, and collaborating with cross-functional teams.