MKS Inc.

2 days ago

Bengaluru, India MKS Inc. Full time

A Day in Your Life at MKS :

As Full Stack Data Engineer, you will partner with data scientists in various business units (ex. Engineering, R&D, Product Marketing etc.) to design data pipelines, create data lakes, and other services using cloud platforms and tools such as AWS, and Azure.

In this role, you will report to the IT Director, Data & Analytics.

Key Responsibilities :

- Design and Development : Design, develop, and maintain scalable and efficient data pipelines and architectures for data ingestion, processing, storage, and analysis.

- Data Integration : Integrate data from various sources, ensuring data consistency and quality.

- Database Management : Develop, optimize, and manage various database systems (both relational and NoSQL), ensuring high performance, availability, and security.

- Machine Learning Integrations : Collaborate with ML engineers to build data pipelines that feed and operationalize

machine learning models, ensuring data quality and feature engineering for model training and inference.

- Data Transformation : Implement sophisticated data transformation, cleaning, and validation processes to prepare raw data for advanced analytics and machine learning applications.

- Front-End Development : Develop intuitive and interactive user interfaces and dashboards for data visualization, reporting, and exploration, making data accessible to a wide audience.

- Back-End Development : Build and maintain scalable APIs and services for secure and efficient data access, manipulation, and integration with other applications.

- Collaboration : Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.

- Performance Optimization : Optimize data systems for performance, scalability, and reliability.

- Documentation : Maintain comprehensive documentation of data systems, processes, and workflows.

Required Skills :

- Programming Languages : Strong proficiency in Python is essential. Experience with Java or Scala is also highly valued.

- Database Technologies : Experience with SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB).

- Machine Learning Fundamentals : Understanding of machine learning concepts, data preprocessing for ML, and

experience with relevant Python libraries (e.g., scikit-learn, TensorFlow, PyTorch).

- Cloud Platforms : Hands-on experience with major cloud service providers (e.g., AWS, Azure, Google Cloud), including their data and compute services.

- Data Processing Frameworks : Knowledge of frameworks like Apache Spark, Hadoop, or Kafka.

- Front-End Technologies : Familiarity with front-end technologies such as HTML, CSS, JavaScript, and frameworks like React or Angular.

- APIs : Experience in building and consuming RESTful APIs.

- Data Visualization : Skills in data visualization tools like Tableau, Power BI, or D3.js.

- Problem-Solving : Strong analytical and problem-solving skills.

- Communication : Excellent communication and collaboration abilities.

Preferred Qualifications :

- Education : bachelor's or master's degree in computer science, Data Engineering, or a related field.

- Experience : Required minimum experience of 2 to 5 years of related experience in a similar role or in software engineering, data engineering, or full-stack development.

- Certifications : Relevant certifications in data engineering or cloud platforms.


(ref:hirist.tech)

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