Job Summary

We are seeking an experienced Data Engineer with strong expertise in cloud data engineering, distributed processing, and modern data platforms to design, build, and maintain scalable data solutions. The ideal candidate will have hands-on experience with Snowflake, Python, SQL, Azure, Apache Spark, Databricks, Kubernetes, and Airflow, along with exposure to CI/CD practices and AI/ML model deployment workflows.

The candidate will play a key role in developing enterprise data pipelines, enabling analytics capabilities, optimizing data platforms, and supporting healthcare data initiatives with secure, reliable, and scalable solutions.

Responsibilities

- Design, develop, and maintain scalable data pipelines and data processing frameworks.
- Build and optimize data solutions using Snowflake, Azure, Spark, and Databricks.
- Develop robust ETL/ELT workflows to ingest, transform, and process large volumes of structured and unstructured data.
- Write efficient and optimized SQL queries for data extraction, transformation, and analytics.
- Develop Python-based data processing applications and automation scripts.
- Work with Apache Spark for large-scale distributed data processing and performance optimization.
- Design and manage data workflows using Apache Airflow.
- Deploy and manage data applications using Kubernetes and cloud-native technologies.
- Implement CI/CD pipelines using GitHub and related DevOps practices.
- Collaborate with data analysts, data scientists, architects, and business teams to deliver analytics solutions.
- Support AI/ML initiatives by enabling data pipelines and assisting with model deployment workflows.
- Build and maintain data models, datasets, and analytical solutions to support business intelligence requirements.
- Perform data quality checks, validation, monitoring, and troubleshooting of production data pipelines.
- Optimize data platform performance, scalability,



and reliability.
- Implement security, governance, and compliance best practices for enterprise healthcare data.
- Participate in architecture discussions, code reviews, and continuous improvement initiatives.

Education

- Bachelor s degree in Computer Science, Engineering, Information Technology, Data Science, or related field.

Experience

- 5+ years of experience in Data Engineering roles.
- Strong experience building enterprise-scale data pipelines and analytics platforms.
- Experience working with cloud-based data solutions and distributed processing environments.
- Healthcare domain experience is preferred.

Required Technical Skills

Data Engineering Cloud Platforms

- Snowflake
- Microsoft Azure
- Apache Spark
- Databricks (Preferred)
- Data Lake / Lakehouse architectures
- ETL/ELT development
- Data pipeline design and optimization

Programming Databases

- Strong programming experience with Python
- Advanced SQL skills
- Experience with data transformation, optimization, and performance tuning

Workflow Orchestration

- Apache Airflow
- Workflow scheduling and dependency management
- Pipeline monitoring and troubleshooting

Containerization DevOps

- Kubernetes
- Docker (Preferred)
- GitHub
- CI/CD pipeline development and automation
- Version control best practices

AI/ML Engineering

- Experience supporting AI/ML workflows
- Understanding of model deployment processes
- Experience integrating ML models into production data platforms is preferred

Data Analytics





- Strong understanding of data analytics concepts
- Ability to support reporting, visualization, and business intelligence requirements
- Experience working with analytical datasets and data models

Preferred Skills

- Experience working with healthcare data platforms, claims, clinical, member, or provider data.
- Knowledge of healthcare data standards and compliance requirements.
- Experience with Azure services such as Azure Data Factory, Azure Databricks, Azure Storage, and Azure Synapse.
- Experience implementing data governance, security, and data quality frameworks.
- Familiarity with modern cloud-native architecture patterns.
- Experience working in Agile/Scrum environments.

Key Competencies

- Data Engineering Architecture
- Cloud Data Platforms
- Data Pipeline Development
- Distributed Computing
- Data Analytics
- Performance Optimization
- Problem Solving
- Automation DevOps Practices
- Data Quality Management
- Collaboration Communication
- Healthcare Data Understanding

What youll do

- Own delivery for client-facing web, mobile, AI, cloud or digital transformation work based on the role.
- Collaborate with project managers, designers, QA and client stakeholders through discovery, build, launch and support.
- Write clear documentation, communicate risks early and keep delivery quality high.
- Contribute to reusable engineering practices, reviews and mentoring inside the WebSenor team.

What were looking for

- Robust hands-on experience relevant to this role and a portfolio of shipped production work.

Location

Hybrid remote in Noida, Uttar Pradesh (Noida).

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Data Engineer 1 - WebSenor (Noida)
🏢 WebSenor
📍 Noida