Senior Software Engineer - Data Engineering
ABOUT THE COMPANY
Teikametrics' AI-powered Marketplace Optimization platform help sellers and brand owners to maximize their potential on the world's most valuable marketplaces. Founded in 2015, Teikametrics uses Proprietary AI technology to maximize profitability in a simple SaaS interface. Teikametrics optimizes more than $8 billion in GMV across thousands of sellers around the world, with brands including Munchkin, mDesign, Clarks, Nutribullet, Conair, Nutrafol, and Solo Stove trusting Teikametrics to unlock the full potential of their selling and advertising on Amazon, Walmart and other marketplaces.
Teikametrics continues to grow exponentially, with teams spanning 3+ countries. We are financially strong, continuously meeting or exceeding revenue targets, and we invest heavily in strengthening the foundation of our organization.
ABOUT THE ROLE
Teikametrics is looking for a Senior Software Engineer - Data Engineering with strong computer science fundamentals and a background in data engineering, API Integration, or large-scale data processing. This role involves designing, developing, and scaling robust data pipelines to process massive amounts of structured and unstructured data. The candidate will work closely with data scientists, analysts, and product engineers to deliver high-performance, scalable solutions.
The architecture and stack evolve continuously as we scale to cater to an ever-growing customer base. Our technology stack includes Databricks, Spark (Scala), Kafka, AWS S3, and other distributed computing tools.
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
Press Reference about Teika
The job description is representative of typical duties and responsibilities for the position and is not all-inclusive. Other duties and responsibilities may be assigned in accordance with business needs. We are proud to be an equal opportunity employer. A background check will be conducted after a conditional offer of employment is extended. #LI-Remote
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Senior Software Engineer - Data Engineering
ABOUT THE COMPANY
Teikametrics' AI-powered Marketplace Optimization platform help sellers and brand owners to maximize their potential on the world's most valuable marketplaces. Founded in 2015, Teikametrics uses Proprietary AI technology to maximize profitability in a simple SaaS interface. Teikametrics optimizes more than $8 billion in GMV across thousands of sellers around the world, with brands including Munchkin, mDesign, Clarks, Nutribullet, Conair, Nutrafol, and Solo Stove trusting Teikametrics to unlock the full potential of their selling and advertising on Amazon, Walmart and other marketplaces.
Teikametrics continues to grow exponentially, with teams spanning 3+ countries. We are financially strong, continuously meeting or exceeding revenue targets, and we invest heavily in strengthening the foundation of our organization.
ABOUT THE ROLE
Teikametrics is looking for a Senior Software Engineer - Data Engineering with strong computer science fundamentals and a background in data engineering, API Integration, or large-scale data processing. This role involves designing, developing, and scaling robust data pipelines to process massive amounts of structured and unstructured data. The candidate will work closely with data scientists, analysts, and product engineers to deliver high-performance, scalable solutions.
The architecture and stack evolve continuously as we scale to cater to an ever-growing customer base. Our technology stack includes Databricks, Spark (Scala), Kafka, AWS S3, and other distributed computing tools.
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
Press Reference about Teika
The job description is representative of typical duties and responsibilities for the position and is not all-inclusive. Other duties and responsibilities may be assigned in accordance with business needs. We are proud to be an equal opportunity employer. A background check will be conducted after a conditional offer of employment is extended. #LI-Remote