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Sentienz
Sentienz cover picture
Founded :
2016
Type :
Products & Services
Size :
20-100
Stage :
Bootstrapped
About

Sentienz is a technology company specializing in next-generation IT engineering solutions. They focus on AI, Data Analytics, Distributed Computing, Product Development, Platform Development, and IoT. The company has recently won the Startup Trailblazer category at LEAP India Startup Summit 2024 for their product Akiro

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Tech stack
Apache Spark
skill iconScala
skill iconPython
skill iconJava
Candid answers by the company
What does the company do?
What is the location preference of jobs?
What is the company's market position and stability?

Sentienz is a technology company founded in 2016 that specializes in two core areas:

  1. Product:
  • Akiro - An AI-powered platform for IoT connectivity, focusing on smart meters, EV systems, and utilities 
  1. Technology Services:
  • AI & Data Intelligence solutions
  • Product & Platform Development
  • DevOps & MLOps services 

Think of Sentienz as a tech partner that helps businesses:

  • Build and scale their technology products
  • Implement AI and data analytics solutions
  • Modernize their IT operations

They primarily serve industries like finance, healthcare, telecom, and smart cities, with their headquarters in Bangalore. The company has grown to 11-50 employees and recently won recognition as a Startup Trailblazer at LEAP India Startup Summit 2024.

Company social profiles
linkedin

Jobs at Sentienz

Sentienz
at Sentienz
3 candid answers
Nikita Sinha
Posted by Nikita Sinha
Bengaluru (Bangalore)
6 - 8 yrs
Upto â‚ą35L / yr (Varies
)
skill iconPython
skill iconScala
Spark
NOSQL Databases
SQL

Key Responsibilities

  • Design, develop, and optimize data pipelines using Apache Spark to process large volumes of structured and unstructured data.
  • Write efficient and maintainable code in Scala and Python for data extraction, transformation, and loading (ETL) operations.
  • Collaborate with cross-functional teams to define data engineering solutions to support analytics and machine learning initiatives.
  • Implement and maintain data lake and warehouse solutions using cloud platforms (e.g., AWS, GCP, Azure).
  • Ensure data workflows and distributed systems' performance, scalability, and reliability.
  • Perform data quality assessments, implement monitoring, and improve data governance practices.
  • Assist in migrating and refactoring legacy data systems into modern distributed data processing platforms.
  • Provide technical leadership and mentorship to junior engineers and contribute to best practices in coding, testing, and deployment.

Qualifications

  • Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.
  • 6+ years of hands-on experience in data engineering, with strong skills in Apache Spark, Scala, and Python.
  • Experience with distributed data processing frameworks and real-time data processing.
  • Strong experience with big data technologies such as Hadoop, Hive, and Kafka.
  • Proficient with relational databases (SQL, PostgreSQL, MySQL) and NoSQL databases (Cassandra, HBase, MongoDB). 
  • Knowledge of CI/CD pipelines and DevOps practices for deploying data workflows.
  • Strong problem-solving skills and experience with optimizing large-scale data systems.
  • Excellent communication and collaboration skills.
  • Experience with orchestration tools like Airflow
  • Experience with containerization and orchestration (e.g., Docker, Kubernetes)


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Sentienz
at Sentienz
3 candid answers
Nikita Sinha
Posted by Nikita Sinha
Bengaluru (Bangalore)
8 - 12 yrs
Upto â‚ą40L / yr (Varies
)
skill iconScala
Spark
skill iconPython
SQL
NOSQL Databases

Key Responsibilities

  • Design, develop, and optimize data pipelines using Apache Spark to process large volumes of structured and unstructured data.
  • Write efficient and maintainable code in Scala and Python for data extraction, transformation, and loading (ETL) operations.
  • Collaborate with cross-functional teams to define data engineering solutions to support analytics and machine learning initiatives.
  • Implement and maintain data lake and warehouse solutions using cloud platforms (e.g., AWS, GCP, Azure).
  • Ensure data workflows and distributed systems' performance, scalability, and reliability.
  • Perform data quality assessments, implement monitoring, and improve data governance practices.
  • Assist in migrating and refactoring legacy data systems into modern distributed data processing platforms.
  • Provide technical leadership and mentorship to junior engineers and contribute to best practices in coding, testing, and deployment.

Qualifications

  • Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.
  • 8+ years of hands-on experience in data engineering, with strong skills in Apache Spark, Scala, and Python.
  • Experience with distributed data processing frameworks and real-time data processing.
  • Strong experience with big data technologies such as Hadoop, Hive, and Kafka.
  • Proficient with relational databases (SQL, PostgreSQL, MySQL) and NoSQL databases (Cassandra, HBase, MongoDB). 
  • Knowledge of CI/CD pipelines and DevOps practices for deploying data workflows.
  • Strong problem-solving skills and experience with optimizing large-scale data systems.
  • Excellent communication and collaboration skills.
  • Experience with orchestration tools like Airflow
  • Experience with containerization and orchestration (e.g., Docker, Kubernetes)


Read more
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