Data Engineer

Nectar is an AI-first product company building intelligent platforms that transform how enterprises leverage AI, automation, and connected technologies. Our products combine Generative AI, Agentic AI, IoT, and cloud-native technologies to deliver intelligent, scalable, and secure experiences for customers worldwide.

At Nectar, we continuously innovate and enhance our core product platform, enabling organizations to unlock actionable insights, automate operations, and make data-driven decisions in real time.

As a Data Engineer at Nectar, you will play a key role in building and scaling the data foundation that powers our intelligent product platform. You will design, develop, and maintain robust data pipelines and data platforms that process large volumes of IoT and application data in real time.

You will collaborate closely with AI engineers, backend developers, product teams, and platform engineers to ensure high-quality, reliable, and accessible data across the organization. This role offers an opportunity to work on cutting-edge technologies while contributing directly to the evolution of our AI and IoT product ecosystem.

• Develop, maintain, and optimize scalable batch and real-time data pipelines.
  
• Build and manage data ingestion frameworks for IoT devices, applications, and third-party systems.
  
• Design and implement robust ETL/ELT processes to support analytics and AI workloads.
  
• Collaborate with AI and product teams to prepare and deliver high-quality datasets for machine learning and Generative AI applications.
  
• Develop and maintain data models, schemas, and storage solutions for structured and unstructured data.
  
• Ensure data quality, reliability, consistency, and availability across the platform.
  
• Monitor and troubleshoot data pipelines, ensuring timely resolution of production issues.
  
• Optimize data processing workflows for performance, scalability, and cost efficiency.
  
• Work with cross-functional teams to understand business requirements and translate them into scalable data solutions.
  
• Implement data governance, security, and access control best practices.
  
• Participate in code reviews, architecture discussions, and continuous platform improvements.
  

• 1+ years of hands-on experience in Data Engineering or related roles.
  
• Strong programming skills in Python and SQL.
  
• Experience building ETL/ELT pipelines and processing large datasets.
  
• Familiarity with data warehousing concepts and modern data architectures.
  
• Experience working with relational and NoSQL databases.
  
• Understanding of real-time and streaming data processing concepts.
  
• Basic experience with cloud platforms such as AWS, Azure, or GCP.
  
• Familiarity with data orchestration and workflow management tools.
  
• Experience using Git and modern software development practices.
  
• Strong analytical and problem-solving skills.
  
• Good communication and collaboration skills with the ability to work in cross-functional teams.
  

• Programming Languages: Python, SQL
  
• Data Processing: Pandas, PySpark, Apache Spark
  
• Data Pipelines & Orchestration: Apache Airflow, Dagster
  
• Streaming & Messaging: Apache Kafka, MQTT, RabbitMQ
  
• Databases: PostgreSQL, MySQL, MongoDB, Redis
  
• Data Warehousing: Snowflake, BigQuery, Amazon Redshift
  
• Cloud Platforms: AWS, Azure, or GCP
  
• Storage Technologies: Data Lakes, Object Storage, Parquet
  
• DevOps & Deployment: Docker, Git, CI/CD
  
• Monitoring & Observability: Grafana, Prometheus, Logging Frameworks
  

• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.
  
• Relevant certifications or hands-on project experience in Data Engineering or Cloud technologies will be an added advantage.
  

• Experience working with IoT data, telemetry systems, or real-time analytics platforms.
  
• Familiarity with lakehouse architectures and modern data platforms.
  
• Exposure to machine learning data pipelines and AI/ML workflows.
  
• Experience with Spark, Kafka, or distributed data processing systems.
  
• Contributions to open-source projects, technical blogs, or engineering communities are a plus.
  

• Build and scale the data platform that powers Nectar's intelligent product ecosystem.
  
• Work on challenging problems involving IoT, AI, real-time analytics, and large-scale data processing.
  
• Collaborate with a passionate and innovative product engineering team.
  
• Gain end-to-end ownership of data systems—from ingestion to analytics and AI enablement.
  
• Continuous learning opportunities, certifications, and career growth in data and platform engineering.
  
• Work in a fast-paced environment where your contributions have visible and lasting impact.