Senior data engineer

3 weeks ago

Vapi, India Meril Full time

Job Summary As a Senior Data Engineer in the AI domain, you will be responsible for designing, building, and optimizing large-scale data pipelines, ensuring high data quality, and enabling seamless integration with AI and machine learning models. You will collaborate closely with data scientists, ML engineers, and other cross-functional teams to deliver scalable data solutions that power AI innovations. Key Responsibilities Design and implement data pipelines for processing large volumes of structured and unstructured data. Build, maintain, and optimize ETL processes for AI and machine learning projects. Develop and maintain scalable data architectures to support real-time and batch processing of data for AI applications. Ensure data integrity, consistency, and security across different data sources and storage systems. Collaborate with AI/ML teams to understand data requirements and provide data engineering solutions to support model training and deployment. Implement and manage data storage solutions such as data lakes, data warehouses, and No SQL databases. Perform data cleansing, transformation, and aggregation to ensure high data quality. Optimize data processing workflows for performance, scalability, and cost-efficiency. Monitor, troubleshoot, and resolve issues related to data pipelines and infrastructure. Mentor and provide guidance to junior data engineers. Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field. 3-5 years of experience as a Data Engineer, with a focus on building data solutions for AI/ML applications. Expertise in programming languages such as Python, Java, or Scala for data processing. Strong experience with big data technologies like Hadoop, Spark, Kafka, and distributed data systems. Proficiency in SQL and experience with relational databases like Postgre SQL, My SQL, etc. Hands-on experience with cloud platforms (AWS, Azure, GCP) and their data engineering services (e.g., Redshift, Big Query, Data Flow, etc.). Familiarity with containerization and orchestration tools like Docker, Kubernetes. Experience with data modeling, data warehousing, and No SQL databases (e.g., Cassandra, Mongo DB). Solid understanding of AI and machine learning data requirements and workflows. Familiarity with version control systems such as Git. Excellent problem-solving skills, with attention to detail and a focus on delivering high-quality solutions. Strong communication and collaboration skills, with experience working in cross-functional teams.

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