Senior Data Engineering Lead

New

Skills

Data Engineering Engineer Etl Java Kafka Machine Learning Python Scala Software Engineering TensorFlow

Join Teikametrics as a Senior Software Engineer - Data Engineering and help shape the future of AI-powered marketplace optimization. As part of a rapidly growing, remote-friendly team, you will be responsible for architecting and scaling robust data pipelines that support advanced analytics and machine learning for some of the world’s top e-commerce brands. Collaborate with experts across data science, engineering, and product to develop best-in-class data solutions on a cloud-native stack.

Job Overview
  • Design and implement scalable, fault-tolerant data pipelines for both real-time and batch processing.
  • Work closely with cross-functional teams to integrate AI/ML models into production environments.
  • Support and optimize the data ecosystem for maximum performance and reliability.
  • Contribute to the evolution of a modern, distributed data architecture using cutting-edge technologies.
  • Enjoy a flexible remote work policy, generous benefits, and opportunities for professional growth.
Key Responsibilities
  • Develop, optimize, and maintain Databricks Spark pipelines for large-scale data processing.
  • Build and manage ETL processes to integrate diverse data sources.
  • Implement data validation, governance, and quality assurance mechanisms.
  • Collaborate with data scientists and ML engineers to deploy AI/ML models efficiently.
  • Leverage real-time streaming technologies (e.g., Kafka) for event-driven data processing.
  • Document technical workflows and best practices to facilitate knowledge sharing.
Required Skills & Qualifications
  • 4+ years of experience in software or data engineering with distributed data systems.
  • Hands-on experience with Apache Spark (Scala or Python) and Databricks.
  • Proficiency in Java, Scala, or Python for scalable data solutions.
  • Expertise in real-time data streaming technologies (Kafka, Flink, or Kinesis).
  • Strong understanding of cloud architectures (AWS, GCP, or Azure), especially S3 and Lambda.
  • Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Familiarity with SQL and NoSQL databases for structured and unstructured data.
  • Knowledge of data warehousing principles and large-scale ETL best practices.
  • Ability to write well-designed, testable, and scalable AI/ML pipelines.
  • Passion for collaboration, learning, and mentoring in a fast-paced environment.

Job Type: Remote

Salary: Not Disclosed

Experience: Entry

Duration: 12 Months

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