Senior Data Engineer

This job will provide you with an opportunity to further your career alongside some of the best and most passionate technology experts from around the world in a leading company within the test, measurement and data analytics industry. You will be a strong contributor collaborating closely with colleagues from various business functions.

At HBK, we live up to our three values: Be True, Own It and Aim High. We believe in absolute integrity - it s how we win for stakeholders, the environment and each other. We believe in teamwork and keeping our promises - to ourselves and others. Finally, we believe in being bold and positive. This is how we perform at our best and achieve greater success.

As a Senior Data Engineer at HBK, you will play a key role in our Platform Team. This position is responsible for designing, developing, and maintaining scalable enterprise applications, data intensive applications and data capabilities. You will work closely with cross-functional teams in a fully remote, self-organizing, agile environment, ensuring that HBKs development practices and quality standards are met. As a Senior Data Engineer, you will also mentor junior team members and participate in architectural discussions to shape the future of HBKs technology stack. This role is based in Chennai, India; however, you can work full-time remotely from anywhere in India. Additionally, periodic collaboration at our Chennai office is required for senior team meetings and offsite collaboration.

Responsibilities:

Core Development and Technology:

Value-Driven Delivery: Rapidly deliver incremental, high-impact data solutions through thin slices of value. Ensure continuous feedback loops and iterative improvements, balancing speed, scalability, and long-term maintainability.

Collaborate closely with stakeholders to prioritize impactful features, balancing speed, scalability, and long-term maintainability.

Enterprise Applications: Design and build scalable, high-performance enterprise applications that meet HBKs quality and performance standards.

Coding Standards: Write clean, maintainable, and efficient code following industry best practices and coding standards.

Code Reviews: Conduct and participate in code reviews. Provide constructive feedback, mentor junior developers during the review process, and ensure adherence to coding standards. Lead initiatives to improve code review processes and establish best practices.

Feature Implementation: Implement new features and enhancements based on requirements and feedback from stakeholders with minimal supervision or guidance.

Testing: Ensure built-in quality across software products by conducting unit, component, functional, and non-functional testing, in harmony with DevOps practices and adhering to Test-Driven Development (TDD) principles.

Agile Collaboration:

Team Engagement: Actively participate in daily stand-ups, sprint planning, retrospectives, and other Agile ceremonies.

Pair Programming: Engage in and promote pair programming, providing mentorship to team members to enhance code quality, share knowledge, and improve team collaboration.

Sprint Goals: Work as a team to achieve sprint goals and deliverables through effective collaboration, ensuring alignment with business objectives. Complete own tasks efficiently while mentoring and supporting junior team members.

Backlog Refinement: Participate in backlog refinement sessions to clarify requirements and plan future work.

Continuous Improvement: Drive continuous improvement initiatives within the team, leveraging experience to identify and implement best practices.

Tech Stack and Innovation:

Technology Exploration and Deployment: Continuously explore, evaluate, and successfully deploy new technologies, tools, and frameworks that can improve the development process or product quality.

Cross-Stack Development: Work across different layers of the technology stack, from front-end to back-end, as needed.

Prototyping: Create prototypes to explore new ideas and validate potential solutions.

Tech Debt Management: Identify and address technical debt to maintain codebase health and performance.

DevOps Culture:

Utilize and maintain existing CI/CD pipelines to ensure smooth and efficient deployment processes.

Infrastructure Management: Work with infrastructure tools and services to manage deployment, monitoring, and maintenance of applications.

Incident Response: Participate in and take ownership of incident response and troubleshooting to ensure high availability and reliability of production systems.

Performance Monitoring: Monitor application performance and optimize code and infrastructure to meet performance requirements.

Solution Development and Integration:

Technical Guidance: Provide technical guidance for solution development and integration, ensuring adherence to relevant strategies, standards, and security practices.

Architecture Discussions: Actively contribute to architectural discussions, ensuring effective and accountable input towards the design and architecture of scalable and robust solutions and systems.

Roadmaps and Improvements: Contribute to product roadmaps and identify areas for improvement or synergy within the development process.

Team Leadership and Development:

Mentorship: Offer support, guidance, and mentorship to junior team members, fostering their professional growth and development.

Task Assignment: Assist in assigning tasks and responsibilities to ensure efficient workflow.

Performance Management: Offer support and constructive feedback to team members, fostering their development and success.

Recruitment and Onboarding: Assist in the recruitment and onboarding of new team members, ensuring alignment with our team culture and values."

Professional Development: Promote a culture of continuous learning and innovation within the team.

Stakeholder Management:

Communication: Collaborate and communicate effectively with stakeholders to ensure that product requirements and features are clearly understood and implemented.

Demos and Feedback: Conduct product demos and gather feedback from stakeholders to continuously improve and refine the product.

Skill Requirements:

Undergraduate degree in Computer Science or a related field, or equivalent practical experience.

4 to 8 years of experience in designing and developing scalable data-intensive applications using technologies such as JavaScript, Python, or any other relevant language.

Data Engineering & Architecture: Experience working with designing, building, and optimizing scalable data pipelines, ETL processes, and data lakes/warehouses.

Experience with cloud platforms - AWS, Azure, GCP

Databases: Deep understanding of relational and NoSQL databases.

Orchestration & Workflow Management: Hands-on experience with Apache Airflow, Argo Workflows, or other orchestration tools.

ML Data Preparation & Model Training: Expertise in data cleaning, feature engineering, and model training, ensuring high-quality models and reproducible training pipelines.

Exposure to cloud-native technologies like Kubernetes, Docker and Azure.

Proficiency in object-oriented programming, design, and architectural patterns.

Solid grasp of fundamental design principles for building scalable applications.

Experience with Agile methodologies (XP, Scrum, or Kanban).

Experience with automated unit tests and exposure to TDD.

Exhibited self-motivation, accountability, and a proactive approach in independently managing tasks with minimal supervision.

Proven leadership and mentorship skills.

Excellent communication and stakeholder management abilities.

Nice to Haves:

Familiarity with modern front-end frameworks (e.g., React, Angular, Vue.js), and building frontend web-based applications.

Advanced experience in designing and deploying applications across multiple runtime and cloud environments.

MLOps & Model Deployment: Experience in automating model deployment, monitoring, and lifecycle management using frameworks like MLflow, MLRun, TensorFlow, or PyTorch.

Background in open-source contributions.

DevOps & CI/CD: Experience with infrastructure as code, and automated deployments.

Data Governance & Security: Knowledge of data privacy, security best practices, and compliance (GDPR, HIPAA).

Streaming & Real-Time Data Processing: Experience with Kafka, or similar eventdriven architectures.