Lead Data Engineer
Honeywell
Lead Data Engineer
Job Description
Lead Data Engineer
Location: United States | Workplace: Hybrid
Overview
Join Honeywell’s high-performing global data engineering team and play a pivotal role in delivering innovative AI/ML data products for industrial customers. As a Lead Data Engineer, you will tackle challenging projects, leverage cutting-edge AI technologies, and drive significant impact by optimizing operations and fueling growth for our customers across aerospace, building technologies, performance materials, and safety solutions. This hybrid role offers collaboration with world-class experts, professional growth opportunities, and the chance to pioneer AI-driven industrial solutions at a Fortune 100 company.
Key Responsibilities
- Design, build, and optimize scalable data pipelines using tools like Apache Spark, Kafka, and Airflow to ingest, process, and transform large-scale industrial IoT data.
- Lead the development of robust data architectures, including data lakes, warehouses (e.g., Snowflake, Databricks), and real-time streaming systems for AI/ML model deployment.
- Collaborate with data scientists, ML engineers, and domain experts to productionize AI/ML models, ensuring high availability, performance, and data quality.
- Mentor junior engineers, conduct code reviews, and drive best practices in data engineering, CI/CD pipelines, and infrastructure as code (Terraform, Kubernetes).
- Implement data governance, security, and compliance frameworks (e.g., GDPR, NIST) for sensitive industrial datasets.
- Analyze complex operational data from sensors and machinery to derive actionable insights for predictive maintenance and process optimization.
- Partner with cross-functional teams to translate business requirements into technical solutions, delivering measurable ROI.
What Makes This Role Exciting
Be at the forefront of industrial transformation with Honeywell’s advanced AI initiatives. Work on real-world applications that enhance safety, efficiency, and sustainability in critical sectors. Enjoy a collaborative culture, access to state-of-the-art tools, continuous learning through Honeywell’s leadership development programs, and the flexibility of a hybrid model. Make a tangible impact on global industries while advancing your career in a dynamic, innovative environment.
Summary
Joining Honeywell’s data engineering team means being part of a high-performing global team that delivers innovative AI/ML data products for industrial customers. You will have the opportunity to work on challenging projects, leverage the latest AI technologies, and make a significant impact on optimizing operations and driving growth for our customers. The role offers professional growth, collaboration with experts, and the chance to be at the forefront of AI-driven industrial solutions.
Locations
- 715 Peachtree Street, N.E., , Atlanta, GA, US 30308
Salary
60,000 - 120,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Expertise in Python, Scala, or Java for data processingintermediate
- Advanced SQL and data modeling skillsintermediate
- Proficiency in Apache Spark, Kafka, and Flink for streaming dataintermediate
- Experience with cloud data services (e.g., AWS S3, Glue, EMR; Azure Synapse; GCP BigQuery)intermediate
- Knowledge of data orchestration (Airflow, Prefect) and workflow managementintermediate
- Strong understanding of data warehousing (Snowflake, Redshift, BigQuery)intermediate
- Familiarity with ML frameworks (TensorFlow, PyTorch) and MLOps toolsintermediate
- Excellent problem-solving and communication skillsintermediate
- Agile methodologies and version control (Git)intermediate
Required Qualifications
- Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field (experience)
- 5+ years of experience in data engineering roles, with proven expertise in building data pipelines for AI/ML applications (experience)
- 3+ years of leadership experience mentoring teams and driving technical projects in industrial or enterprise environments (experience)
- Hands-on experience with cloud platforms (AWS, Azure, or GCP) and big data technologies (Spark, Hadoop, Kafka) (experience)
- Strong proficiency in Python, SQL, and ETL/ELT processes for handling petabyte-scale datasets (experience)
- Experience with containerization (Docker, Kubernetes) and orchestration tools (Airflow, Kubeflow) (experience)
Preferred Qualifications
- Master's degree in Data Engineering, Machine Learning, or related field (experience)
- Certifications such as AWS Certified Data Analytics, Google Professional Data Engineer, or Databricks Certified Data Engineer (experience)
- Domain knowledge in industrial IoT, manufacturing, or aerospace data systems (experience)
Responsibilities
- Architect and implement end-to-end data pipelines for real-time and batch processing of industrial sensor data
- Lead the optimization of data infrastructure for low-latency AI/ML inference in production environments
- Develop and maintain data quality frameworks, monitoring, and alerting systems to ensure reliability
- Collaborate with product managers and stakeholders to define data requirements and success metrics
- Drive adoption of modern data stack tools and automate deployment processes using DevOps practices
- Conduct performance tuning and cost optimization for cloud-based data workloads
- Stay abreast of emerging AI technologies and integrate them into Honeywell's data ecosystem
Benefits
- general: Competitive base salary and performance-based bonuses
- general: Comprehensive health, dental, and vision insurance with low premiums
- general: 401(k) retirement savings plan with generous company matching
- general: Professional development programs, tuition reimbursement, and leadership training
- general: Flexible hybrid work model with 4-5 weeks of PTO annually
- general: Employee stock purchase plan and wellness incentives
Tags & Categories
Answer 10 quick questions to check your fit for Lead Data Engineer @ Honeywell.
Related Books and Jobs
Lead Data Engineer
Honeywell
Lead Data Engineer
Job Description
Lead Data Engineer
Location: United States | Workplace: Hybrid
Overview
Join Honeywell’s high-performing global data engineering team and play a pivotal role in delivering innovative AI/ML data products for industrial customers. As a Lead Data Engineer, you will tackle challenging projects, leverage cutting-edge AI technologies, and drive significant impact by optimizing operations and fueling growth for our customers across aerospace, building technologies, performance materials, and safety solutions. This hybrid role offers collaboration with world-class experts, professional growth opportunities, and the chance to pioneer AI-driven industrial solutions at a Fortune 100 company.
Key Responsibilities
- Design, build, and optimize scalable data pipelines using tools like Apache Spark, Kafka, and Airflow to ingest, process, and transform large-scale industrial IoT data.
- Lead the development of robust data architectures, including data lakes, warehouses (e.g., Snowflake, Databricks), and real-time streaming systems for AI/ML model deployment.
- Collaborate with data scientists, ML engineers, and domain experts to productionize AI/ML models, ensuring high availability, performance, and data quality.
- Mentor junior engineers, conduct code reviews, and drive best practices in data engineering, CI/CD pipelines, and infrastructure as code (Terraform, Kubernetes).
- Implement data governance, security, and compliance frameworks (e.g., GDPR, NIST) for sensitive industrial datasets.
- Analyze complex operational data from sensors and machinery to derive actionable insights for predictive maintenance and process optimization.
- Partner with cross-functional teams to translate business requirements into technical solutions, delivering measurable ROI.
What Makes This Role Exciting
Be at the forefront of industrial transformation with Honeywell’s advanced AI initiatives. Work on real-world applications that enhance safety, efficiency, and sustainability in critical sectors. Enjoy a collaborative culture, access to state-of-the-art tools, continuous learning through Honeywell’s leadership development programs, and the flexibility of a hybrid model. Make a tangible impact on global industries while advancing your career in a dynamic, innovative environment.
Summary
Joining Honeywell’s data engineering team means being part of a high-performing global team that delivers innovative AI/ML data products for industrial customers. You will have the opportunity to work on challenging projects, leverage the latest AI technologies, and make a significant impact on optimizing operations and driving growth for our customers. The role offers professional growth, collaboration with experts, and the chance to be at the forefront of AI-driven industrial solutions.
Locations
- 715 Peachtree Street, N.E., , Atlanta, GA, US 30308
Salary
60,000 - 120,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Expertise in Python, Scala, or Java for data processingintermediate
- Advanced SQL and data modeling skillsintermediate
- Proficiency in Apache Spark, Kafka, and Flink for streaming dataintermediate
- Experience with cloud data services (e.g., AWS S3, Glue, EMR; Azure Synapse; GCP BigQuery)intermediate
- Knowledge of data orchestration (Airflow, Prefect) and workflow managementintermediate
- Strong understanding of data warehousing (Snowflake, Redshift, BigQuery)intermediate
- Familiarity with ML frameworks (TensorFlow, PyTorch) and MLOps toolsintermediate
- Excellent problem-solving and communication skillsintermediate
- Agile methodologies and version control (Git)intermediate
Required Qualifications
- Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field (experience)
- 5+ years of experience in data engineering roles, with proven expertise in building data pipelines for AI/ML applications (experience)
- 3+ years of leadership experience mentoring teams and driving technical projects in industrial or enterprise environments (experience)
- Hands-on experience with cloud platforms (AWS, Azure, or GCP) and big data technologies (Spark, Hadoop, Kafka) (experience)
- Strong proficiency in Python, SQL, and ETL/ELT processes for handling petabyte-scale datasets (experience)
- Experience with containerization (Docker, Kubernetes) and orchestration tools (Airflow, Kubeflow) (experience)
Preferred Qualifications
- Master's degree in Data Engineering, Machine Learning, or related field (experience)
- Certifications such as AWS Certified Data Analytics, Google Professional Data Engineer, or Databricks Certified Data Engineer (experience)
- Domain knowledge in industrial IoT, manufacturing, or aerospace data systems (experience)
Responsibilities
- Architect and implement end-to-end data pipelines for real-time and batch processing of industrial sensor data
- Lead the optimization of data infrastructure for low-latency AI/ML inference in production environments
- Develop and maintain data quality frameworks, monitoring, and alerting systems to ensure reliability
- Collaborate with product managers and stakeholders to define data requirements and success metrics
- Drive adoption of modern data stack tools and automate deployment processes using DevOps practices
- Conduct performance tuning and cost optimization for cloud-based data workloads
- Stay abreast of emerging AI technologies and integrate them into Honeywell's data ecosystem
Benefits
- general: Competitive base salary and performance-based bonuses
- general: Comprehensive health, dental, and vision insurance with low premiums
- general: 401(k) retirement savings plan with generous company matching
- general: Professional development programs, tuition reimbursement, and leadership training
- general: Flexible hybrid work model with 4-5 weeks of PTO annually
- general: Employee stock purchase plan and wellness incentives
Tags & Categories
Answer 10 quick questions to check your fit for Lead Data Engineer @ Honeywell.
Related Books and Jobs