Honeywell Connected Enterprise (HCE) is the software division of Honeywell with a strategic focus on digitization, sustainability, and OT Cybersecurity SaaS offerings and solutions. Since its inception in 2018, HCE has pioneered intelligent operations through its flagship platform – Honeywell Forge, which unites real-time data across assets, people, and processes into a 360-degree system of record.

As a Sr Advanced Data Engineer, you will help deliver cutting-edge analytics solutions that directly support Honeywell's business success. You will be part of a global team of experts in software engineering, data science, AI, and industrial operations.

Key Responsibilities:

Deliver contemporary analytics solutions for all Honeywell business groups and functions.
Build strong relationships with leadership to deliver data solutions aligned with business needs.
Develop solutions using Databricks, Hive, Hadoop, PostgreSQL, and other platforms.
Identify and implement process improvements and automate repetitive tasks.
Prioritize scalability, performance optimization, and process efficiency.
Collaborate with a cross-functional team (scrum masters, product owners, data engineers, DevOps, etc.).
Participate in full software development lifecycle from idea to production.
Contribute to the development of new platforms using APIs, microservices, and cloud technologies.

You Must Have:

Bachelor's degree in Computer Science, Engineering, Applied Mathematics, or related field.
8–11 years of data engineering experience.
Experience developing and deploying complex big data ingestion jobs using Spark, Informatica BDM, Talend.
At least 5 years of hands-on experience with Spark, Pig/Hive, and automation tools like NiFi or Airflow/Oozie.
Experience processing large volumes of structured/unstructured data, including streaming real-time data (Kafka, Spark Streaming).
Experience with Databricks, Cloudera, Hortonworks, or cloud-based Hadoop (AWS EMR, Azure Data Lake).
Strong communication and articulation skills.

We Value:

Minimum 4+ years of experience with NoSQL systems (HBase, Cassandra, MongoDB, etc.).
Strong understanding of schema design and complex SQL development.
Experience with cloud deployments and container orchestration (Kubernetes, Swarm).
Experience with enterprise systems data (ERPs, CRMs, marketing tools).
Proficiency in dimensional modeling, data warehousing, and data mining.
Familiarity with CI/CD tools (Octopus, Bamboo) and Agile/Scrum practices.
Experience with visualization tools (Tableau, Spotfire, QlikView) and web technologies (Angular.js, D3.js).
Knowledge of database performance management and API development.
Experience collaborating with remote/global teams.
Ability to make timely, data-driven decisions in complex situations.