Director of Data Infrastructure Engineering at RapidAI

RapidAI logo
RapidAI

Director of Data Infrastructure Engineering

in flag
India

Hybrid

Full Time

#Engineering

#Python

#Java

#Scala

#Apache Spark

#Snowflake

#Apache Flink

#Hadoop

#AWS

#GCP

#Azure

RapidAI is looking for a Director of Data Infrastructure Engineering

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Key Responsibilities:
  • Design and implement scalable, reliable, and efficient data infrastructure solutions to support the organization's data processing, storage, and analytics needs.
  • Collaborate with data engineers, software engineers, and data scientists to understand data requirements and translate them into technical specifications and architecture designs.
  • Develop and maintain data pipelines for ingesting, processing, and transforming large volumes of data from various sources, ensuring data quality and integrity.
  • Optimize data storage and retrieval processes, including database schema design, indexing strategies, and query optimization, to enhance performance and reduce latency.
  • Implement monitoring, alerting, and logging mechanisms to proactively identify and troubleshoot issues in the data infrastructure, ensuring high availability and reliability.
  • Stay updated on emerging technologies, tools, and best practices in data engineering and infrastructure management, and recommend adoption as appropriate.
  • Provide technical leadership and mentorship to junior members of the team, fostering a culture of collaboration, learning, and continuous improvement.
  • Work closely with stakeholders to understand business requirements and priorities, 


  • Qualifications:
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • 12-15 years of overall experience with atleast 5+ years in data engineering or infrastructure roles, with a focus on designing and building scalable data platforms.
  • Proficiency in programming languages such as Python, Java, or Scala, and experience with data processing frameworks such as Apache Spark, Snowflake, Apache Flink, or Hadoop.
  • Strong understanding of distributed systems, cloud computing platforms (e.g., AWS, GCP, Azure), and containerization technologies (e.g., Docker, Kubernetes).
  • Experience with relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., Cassandra, MongoDB).
  • Hands-on experience with data pipeline orchestration tools such as Apache Airflow, Luigi, or Prefect.
  • Excellent problem-solving skills and the ability to troubleshoot complex issues in a distributed environment.
  • Strong communication skills and the ability to collaborate effectively with cross-functional teams.
  • Experience with Agile methodologies and DevOps practices is a plus
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