Manager-Data & ML Engg

Job Summary

Manager Data and ML Engineering role focusing on designing building and optimizing scalable data platforms and machine learning solutions using Java advanced JavaScript and advanced Java in a hybrid work model enabling secure high quality data products that power analytics and intelligent applications for global business stakeholders in a collaborative and inclusive environment

Responsibilities

• Architect robust data pipelines and platforms that ingest transform and serve large scale datasets using Java and advanced Java to support analytics and machine learning initiatives for diverse business functions
• Design modular and reusable services and APIs using Java and advanced JavaScript that reliably expose data and ML capabilities to internal applications and external partner systems
• Develop production ready machine learning workflows that manage data preparation feature engineering model training and model deployment while ensuring traceability and reproducibility across environments
• Implement strong data quality controls including validation checks anomaly detection data reconciliation and monitoring to maintain trusted datasets for decision making
• Optimize performance of batch and real time data processing jobs by tuning code parallelization strategies and resource usage to achieve reliable throughput and cost efficiency
• Collaborate closely with data scientists analysts and product teams to translate analytical requirements into scalable engineering solutions that deliver measurable business outcomes
• Establish coding standards review practices and version control workflows that improve reliability maintainability and security of data and ML engineering codebases
• Coordinate with cloud infrastructure and security teams to ensure data pipelines storage layers and ML services adhere to enterprise standards and regulatory expectations
• Create detailed technical documentation for data models transformation logic interface contracts and operational procedures that help teams onboard and maintain solutions efficiently
• Enable robust observability by implementing logging metrics and alerting for data and ML pipelines so that issues are detected early and resolved with minimal business disruption
• Mentor junior engineers by reviewing work sharing best practices and guiding them through complex engineering problems to raise overall team capability and delivery quality
• Drive continuous improvement by evaluating new tools frameworks and design patterns in the Java and JavaScript ecosystem and proposing adoption where they add clear value
• Align engineering activities with organizational sustainability and social impact goals by prioritizing efficient architectures that reduce resource consumption and support ethical use of data

Qualifications

• Demonstrate ten to fourteen years of hands on experience in designing and implementing data intensive applications using Java and advanced Java with strong focus on scalability and reliability
• Exhibit advanced proficiency with modern JavaScript frameworks and tooling to build or integrate front end or service layer components that interact with data and ML platforms
• Apply solid understanding of machine learning lifecycle including feature pipelines model training evaluation and deployment using industry standard tools and libraries
• Show proven experience working in hybrid work models by effectively collaborating across onsite and remote teams using structured communication and documentation practices
• Display strong knowledge of relational and nonrelational databases data warehousing concepts and streaming platforms to support both batch and real time data solutions
• Utilize deep expertise in software engineering fundamentals including algorithms data structures design patterns testing strategies and secure coding practices
• Communicate complex technical concepts clearly to technical and nontechnical stakeholders while gathering feedback and aligning solutions to business objectives