- As a Senior Data Engineer, you will play a key role in designing and implementing data solutions at Bank
- You will be responsible for leading data engineering projects, mentoring junior team members, and collaborating with cross-functional teams to deliver high-quality and scalable data infrastructure.
- Your expertise in data architecture, performance optimization, and data integration will be instrumental in driving the success of our data initiatives.
- Design and develop scalable, high-performance data architecture and data models.
- Collaborate with data scientists, architects, and business stakeholders to understand data requirements and design optimal data solutions.
- Evaluate and select appropriate technologies, tools, and frameworks for data engineering projects.
- Define and enforce data engineering best practices, standards, and guidelines.
- Develop and maintain robust and scalable data pipelines for data ingestion, transformation, and loading for real-time and batch-use-cases.
- Implement ETL processes to integrate data from various sources into data storage systems.
- Optimise data pipelines for performance, scalability, and reliability.
- Identify and resolve performance bottlenecks in data pipelines and analytical systems.
- Monitor and analyse system performance metrics, identifying areas for improvement and implementing solutions.
- Optimise database performance, including query tuning, indexing, and partitioning strategies.
- Implement real-time and batch data processing solutions.
- Implement data quality frameworks and processes to ensure high data integrity and consistency.
- Design and enforce data management policies and standards.
- Develop and maintain documentation, data dictionaries, and metadata repositories.
- Conduct data profiling and analysis to identify data quality issues and implement remediation strategies.
- ML Models Deployment & Management (is a plus)
- Responsible for designing, developing, and maintaining the infrastructure and processes necessary for deploying and managing machine learning models in production environments
- Implement model deployment strategies, including containerization and orchestration using tools like Docker and Kubernetes.
- Optimize model performance and latency for real-time inference in consumer applications.
- Collaborate with DevOps teams to implement continuous integration and continuous deployment (CI/CD) processes for model deployment.
- Monitor and troubleshoot deployed models, proactively identifying and resolving performance or data-related issues.
- Implement monitoring and logging solutions to track model performance, data drift, and system health.
- Lead data engineering projects, providing technical guidance and expertise to team members.
- Conduct code reviews and ensure adherence to coding standards and best practices.
- Mentor and coach junior data engineers, fostering their professional growth and development.
- Collaborate with cross-functional teams, including data scientists, software engineers, and business analysts, to drive successful project outcomes.
- Stay abreast of emerging technologies, trends, and best practices in data engineering and share knowledge within the team.
- Participate in the evaluation and selection of data engineering tools and technologies.
|Job Type ||: || Full Time |
|Role ||: || Experienced |
|Min Salary ||: || 15 Lakh |
|Max Salary ||: || 22 Lakh |
|Experience ||: || 2 to 8 Yrs |
|Locality ||: || Bangalore |
|Eligibility ||: || Btech /BE |
|Company ||: || Private Bank Limited |
Jaina Ruparel Team Leader - Talent Acquisition Manager of Waytogo Consultants Pvt Ltd Member Since November -0001