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Netomi
Netomi
51 – 200 Employees
H1B Visa SponsorConsultingLogisticsMarketing
Netomi develops AI-powered customer experience solutions for enterprise customer service teams. Its Agentic OS connects with existing business systems and uses generative AI and large language models to automate routine inquiries, support agents, and improve service across email, chat, messaging, SMS, social media, search, and voice. The company focuses on secure, proactive, and predictive customer care for global brands, with applications spanning consulting, logistics, and marketing. Netomi’s growing team works on enterprise AI, omnichannel support, and automation technology, creating opportunities for people interested in building practical tools for modern customer service.
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Data Engineer II - Netomi (Remote, India)

Join Netomi as a Data Engineer II building scalable pipelines, data products, and analytics for an agentic AI customer-experience platform. The role supports models, scorecards, and actionable insights for enterprise brands worldwide.

INIndiaRemoteFull-timeMiddleSeniorEnglish RequiredData Engineer
AirflowAmazon RedshiftApacheAWSBigQueryCloudDistributed SystemsDockerETLGoogle Cloud PlatformKafkaKubernetesMySQLPostgresPythonRabbitMQSparkSQL

Description

  • Build secure, reliable, and scalable data pipelines with platforms including Spark, Databricks, Airflow, and Snowflake.
  • Create ETL and ELT workflows that ingest structured and unstructured data.
  • Use exploratory analysis to identify trends, verify data quality, and inform data products and business decisions.
  • Partner with data scientists, analysts, and software engineers to develop models for analytics and real-time insights.
  • Produce maintainable Python code supported by thorough unit and integration testing.
  • Manage feature delivery from development through completion within an agile team.
  • Lead complex data and trend investigations with data science, product, engineering, and customer success stakeholders.
  • Evaluate product operations initiatives and create scorecards and reports to communicate results.
  • Use customer and business data to uncover and pursue improvement opportunities.
  • Help develop policies, processes, and tools that address product quality issues.

Requirements

  • Bachelor’s or master’s degree in computer science, engineering, or a related discipline.
  • At least four years of practical experience in data engineering or backend software development.
  • Strong knowledge of relational databases, including RDS, MySQL, and PostgreSQL.
  • Hands-on experience with Apache Kafka or RabbitMQ for asynchronous, decoupled architectures.
  • Proficiency in Python and SQL, plus experience with a data pipeline orchestration tool such as Apache Airflow, Luigi, or Prefect.
  • Extensive experience with cloud data platforms such as AWS Redshift, Google Cloud BigQuery, Snowflake, or Databricks.
  • Thorough understanding of data modeling, data warehousing, and distributed systems.
  • Familiarity with DevOps practices, including CI/CD, infrastructure as code, and Docker or Kubernetes containerization.
  • Exposure to AI and machine-learning solutions or an interest in partnering with data science teams.
  • Knowledge of data security and privacy requirements, including GDPR and HIPAA.
  • Familiarity with prompt engineering and the way LLM-based systems work with data.

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