Honeywell
Website:
honeywell.com
Job details:
Job Description
We are seeking an experienced Senior Data Engineer to design, build, and optimize scalable data platforms leveraging
Databricks. This role will be responsible for delivering reliable, high ‑ performance data pipelines and analytics-ready datasets, while providing technical leadership and mentoring within the data engineering team.
Responsibilities
Key Responsibilities
- Design and implement scalable data pipelines using Databricks (PySpark, Delta Lake)
- Develop and optimize ELT pipelines loading data for analytics and reporting
- Architect and maintain lakehouse and warehouse solutions following Bronze, Silver, and Gold data layer patterns
- Build batch and streaming pipelines using Databricks Jobs and Spark Structured Streaming
- Design data models optimized for Snowflake (star/snowflake schemas, dimensional modeling)
- Optimize Spark jobs and Snowflake queries for performance and cost efficiency
- Implement data quality checks, monitoring, and data validation across Databricks and Snowflake
- Integrate Databricks and Snowflake with orchestration tools ( Azure Data Factory, etc.)
- Ensure data security, governance, role-based access control, and compliance standards
- Collaborate with Data Analysts and Data Scientists to deliver analytics and ML-ready datasets
- Troubleshoot complex pipeline failures and perform root-cause analysis
- Mentor junior engineers, conduct code reviews, and enforce engineering best practices
- Contribute to data architecture decisions, tooling evaluation, and roadmap planning
- Maintain clear documentation of pipelines, data models, and system architecture
Qualifications
Required Qualifications
- 6+ years of experience in Data Engineering, ETL Development, Database Administration.
- Strong hands-on experience with Databricks in production environments
- Advanced SQL skills and solid expertise in data modeling
- Proficiency in Python , SQL, PySpark
- Strong experience with Apache Spark and PySpark
- Experience working with Delta Lake, schema evolution, and data versioning
- Experience with cloud platforms (AWS, Azure, or GCP)
- Experience building scalable, reliable, fault-tolerant data pipelines
- Solid understanding of distributed data systems
- Experience with streaming platforms (Kafka)
- Exposure to ML pipelines or feature stores (Databricks Feature Store preferred)
Key Skills
- Databricks & Apache Spark
- Snowflake data warehousing
- Lakehouse and Data Warehouse architecture
- Advanced SQL and performance tuning
- Cloud-native data engineering
- Scalability, reliability, and cost optimization
- Technical leadership and mentoring
About Us
Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments – powered by our Honeywell Forge software – that help make the world smarter, safer and more sustainable.
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