Senior Advanced Software Architect

As a Sr Advanced SW Architect here at Honeywell, you will be responsible for leading the architectural design and development of complex software systems, ensuring they align with business objectives and scalability requirements. Your role will involve providing technical guidance to project teams, driving innovation through prototyping, and exploring new technologies to integrate cutting-edge solutions into our software architectures.

In this role, you will impact the strategic direction of our software systems, optimizing their performance and ensuring they meet high standards of reliability and maintainability. By collaborating with cross-functional teams and stakeholders, you will translate business requirements into effective software architectures, directly contributing to customer satisfaction and the overall success of Honeywell in the dynamic technology landscape.

YOU MUST HAVE

• 5+ years of experience in software architecture and development

• Mastery level knowledge in design principles, architectural patterns, and coding standards

WE VALUE

• Bachelor’s degree or higher in Computer Science, Software Engineering, or related field

• Strong leadership and management skills

Sr Advanced Software Engineer

· 8+ years of experience in Data Engineering & Big Data, Spark and Iceberg , with strong exposure to real-world scenarios.

· Strong proficiency in DataBricks

· Strong proficiency in Data Warehousing solutions

· Strong proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn, XGBoost).

· Experience with cloud platforms (Azure, AWS, GCP) and container orchestration (Docker, Kubernetes).

· Knowledge of big data ecosystems (Spark, Hadoop, Databricks) and real-time data streams (Kafka, Flink)

· Proficiency in SQL and NoSQL databases (PostgreSQL, MongoDB, Redis).

· Proficiency in Graph Databases (Noe4j)

· Familiarity with vector databases (FAISS, Pinecone, Weaviate) and embedding techniques.

· Optimize data performance, latency, and resource utilization for production-grade deployments.

· Understanding of CI/CD pipelines and DevOps practices for Data workflows.

· Strong problem-solving mindset with a bias toward experimentation and iteration.

· Excellent communication and stakeholder management skills.

· Ability to evaluate alternative solutions and articulate technical decisions clearly.