Roles and Responsibilities

  • 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 Details

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

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Recruiter Details

Jaina Ruparel

Jaina Ruparel

Team Leader - Talent Acquisition Manager of Waytogo Consultants Pvt Ltd
Member Since November -0001


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