Data Engineer
2 months ago
Job Title : ML - Data Engineer
Location : Gurugram, Haryana
Job Type : Full-Time
Notice period : Immediate Joiners Only
About Us :
Coders Brain is a global leader in its services, digital and business solutions that partners with its clients to simplify, strengthen and transform their businesses. We ensure the highest levels of certainty and satisfaction through a deep-set commitment to our clients, comprehensive industry expertise and a global network of innovation and delivery centers. We achieved our success because of how successfully we integrate with our clients.
- Quick Implementation : We offer quick implementation for the new onboarding client.
- Experienced Team : We've built an elite and diverse team that brings its unique blend of talent, expertise, and experience to make you more successful, ensuring our services are uniquely customized to your specific needs.
- One Stop Solution : Coders Brain provides end-to-end solutions for the businesses at an affordable price with uninterrupted and effortless services.
- Ease of Use : All of our products are user friendly and scalable across multiple platforms. Our dedicated team at Coders Brain implements keeping the interest of enterprise and users in mind.
- Secure : We understand and treat your security with utmost importance. Hence we blend security and scalability in our implementation considering long term impact on business benefit.
Role Overview :
As a Dev+ML+Data Engineer you will be responsible for developing and managing end-to-end machine learning pipelines, ensuring seamless integration and deployment of ML models, and optimizing data processing frameworks. You will work closely with data scientists, engineers, and stakeholders to build robust, scalable, and efficient solutions in a real-time environment.
Key Responsibilities :
Data Engineering & Processing :
- Design, build, and maintain scalable data pipelines using Apache Spark and Spark Streaming for real-time data processing.
- Develop and implement data ingestion, transformation, and enrichment processes to support machine learning workflows.
- Optimize and troubleshoot Spark jobs and streaming pipelines for performance and reliability.
Machine Learning Lifecycle Management :
- Manage the full ML lifecycle, including model development, deployment, monitoring, and maintenance.
- Implement and automate CI/CD pipelines for ML models using frameworks and tools that support continuous integration and delivery.
- Collaborate with data scientists to integrate and operationalize machine learning models into production environments.
Infrastructure & Operations :
- Utilize Docker and Kubernetes to containerize and orchestrate applications and ML models, ensuring scalability and reliability.
- Develop and maintain infrastructure as code (IaC) for efficient deployment and management of resources.
- Monitor system performance and resolve issues related to data processing and ML operations.
Collaboration & Communication :
- Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to understand requirements and deliver solutions that meet business needs.
- Document and communicate technical processes, workflows, and best practices to ensure alignment and knowledge sharing within the team.
Must-Have Skills :
Technologies :
- Proficiency in Apache Spark and Spark Streaming for real-time data processing.
- Experience with ML lifecycle management, including deployment and monitoring of ML models.
- Strong understanding of CI/CD practices and tools specific to ML models.
- Hands-on experience with Docker and Kubernetes for containerization and orchestration.
- Proficiency in Python for data engineering and ML tasks.
- Practical experience in building and managing streaming pipelines.
Soft Skills :
- Strong problem-solving abilities and analytical skills.
- Excellent communication skills with the ability to convey complex technical concepts to non-technical stakeholders.
- Ability to work effectively both independently and in a collaborative team environment.
Nice-to-Have Skills : Experience with Scala for Spark applications and data processing tasks.
Office Requirements :
Initial Onboarding : The position requires a mandatory in-office presence for the first month of onboarding.
Post-Onboarding : Flexible work arrangement with an expectation of 50% office presence per month thereafter.
Education & Experience : Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
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