Honeywell Hiring Advanced Data Engineer Job in Bengaluru | Apply Now 2024

An Advanced Data Engineer designs and optimizes data pipelines, architects scalable data solutions, manages big data platforms, ensures data quality and security, and collaborates with cross-functional teams to enable data-driven decision-making and advanced analytics within an organization.

Job Role: Advanced Data Engineer
Salary: Not Disclosed
Location: Bengaluru, Karnataka
Company: Honeywell
Qualifications: Bachelor’s Degree

About Company:

Advanced Data Engineer

Honeywell, a multinational conglomerate, specializes in various industries including aerospace, building technology, and overall performance substances. Founded in 1906, the employer has developed into a global chief in revolutionary technology for homes, companies, and governments. Their products vary from aircraft engines and clever thermostats to industrial protection answers. Honeywell’s commitment to efficiency, protection, and sustainability drives its research and improvement efforts, making it dependent on associate international. With a focus on enhancing productivity and high-quality lifestyles, Honeywell keeps forming industries with modern-day answers and offerings.

Role Overview:

Join Honeywell in Bengaluru as an Advanced Data Engineer, contributing to progressive and eco-friendly answers. With a focus on robust and scalable data structure, you will lay out and enforce records models, broaden ETL/ELT pipelines, and optimize Snowflake performance. Collaborate with move-useful teams, conduct code reviews, and troubleshoot technical troubles. Required qualifications encompass 6+ years of experience, sturdy SQL and Snowflake competencies, and talent in programming languages like Python or Java. Cloud revel in with AWS or Azure is critical. Embrace dynamic career opportunities in a function in which creativity and enterprise high-quality practices pressure fulfillment.

Roles and Responsibilities Of Advanced Data Engineer:

As an Advanced Data Engineer, your pinnacle roles and responsibilities commonly include:

Architecting Data Systems: Designing and implementing sturdy, scalable, and green statistics pipelines and architectures to guide numerous statistics-intensive packages and analytics.

Data Integration: Ensuring seamless integration of records from more than one asset, consisting of databases, APIs, and streaming systems, while maintaining information fine and integrity.

Performance Optimization: Identifying bottlenecks and optimizing information processing and garage systems for advanced overall performance, reliability, and price performance.

Data Security and Compliance: Implementing and preserving security features to protect touchy facts, ensuring compliance with guidelines along with GDPR, HIPAA, or industry-precise requirements.

Collaboration and Communication: Collaborating with cross-functional teams, including statistics scientists, analysts, and enterprise stakeholders, to apprehend requirements and deliver solutions that meet business needs. Effective communication of complicated technical principles to non-technical stakeholders is also critical.

Skills Required For Advanced Data Engineer :

here are the pinnacle 5 abilities of a complicated information engineer:

Advanced Data Engineer

Expertise in Big Data Technologies:

Advanced records engineers have to be gifted in operating with large facts frameworks like Hadoop, Spark, and Kafka. They ought to realize the way to design, implement, and optimize information pipelines with the use of this technology.

Programming Proficiency: Strong programming abilities are critical, especially in languages like Python, Scala, or Java. Engineers must be adept at writing green code to control and examine big datasets.

Data Modeling and Database Management:

Advanced records engineers should have a deep knowledge of database systems, consisting of relational databases like SQL and NoSQL databases like MongoDB or Cassandra. They must be professional in data modeling, schema design, and optimizing database performance.

Machine Learning and AI:

Knowledge of gadget-mastering algorithms and strategies is increasingly critical for statistics engineers. They must be capable of integrating systems gaining knowledge of fashions into information pipelines and leveraging AI technology for facts processing and analysis.

Problem-Solving and Troubleshooting:

Advanced information engineers should possess sturdy trouble-solving capabilities and the potential to troubleshoot complex issues in statistics pipelines and systems. This consists of debugging code, optimizing performance, and ensuring facts are excellent and reliable.