Senior Software Engineer

HOW YOU'LL SPEND YOUR TIME

• Design and implement highly scalable, fault-tolerant data pipelines for real-time and batch processing.
• Develop and optimize end-to-end Databricks Spark pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.
• Build and manage ETL (Extract, Transform, Load) processes to integrate data from diverse sources into our data ecosystem.
• Implement data validation, governance, and quality assurance mechanisms to ensure accuracy, completeness, and reliability.
• Collaborate with data scientists, ML engineers, and analysts to integrate AI/ML models into production environments, ensuring efficient data pipelines for training, deployment, and monitoring.
• Work with real-time data streaming solutions such as Kafka, Kinesis, or Flink to process and analyze event-driven data.
• Improve and optimize performance, scalability, and efficiency of data workflows and storage solutions.
• Document technical designs, workflows, and best practices to facilitate knowledge sharing and maintain system documentation.

WHO YOU ARE

• 4+ years of experience as a professional software/data engineer, with a strong background in building large-scale distributed data processing systems.
• Experience with AI, machine learning, or data science concepts, including working on ML feature engineering, model training pipelines, or AI-driven data analytics.
• Hands-on experience with Apache Spark (Scala or Python) and Databricks.
• Experience with real-time data streaming technologies such as Kafka, Flink, Kinesis, or Dataflow.
• Proficiency in Java, Scala, or Python for building scalable data engineering solutions.
• Deep understanding of cloud-based architectures (AWS, GCP, or Azure) and experience with S3, Lambda, EMR, Glue, or Redshift.
• Experience in writing well-designed, testable, and scalable AI/ML data pipelines that can be efficiently reused and maintained with effective unit and integration testing.
• Strong understanding of data warehousing principles and best practices for optimizing large-scale ETL workflows.
• Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Optimize ML feature engineering and model training pipelines for scalability and efficiency.
• Knowledge of SQL and NoSQL databases for structured and unstructured data storage.
• Passion for collaborative development, continuous learning, and mentoring junior engineers.

WHAT CAN HELP YOU STAND OUT

• Exposure to MLOps or Feature Stores for managing machine learning model data.
• Experience with data governance, compliance, and security best practices.
• Experience working in a fast-paced startup environment.

WE'VE GOT YOU COVERED

• Every Teikametrics employee is eligible for company equity
• Remote Work – flexibility to work from home or from our offices + remote working allowance
• Broadband reimbursement 
• Group Medical Insurance – Coverage of INR 7,50,000 per annum for a family 
• Crèche benefit
• Training and development allowance