Walk-in Interview|Sr. Data Engineer/Data Engineer

• Design, build, and maintain robust data pipelines and ETL processes to support data integration, transformation, and storage.
• Develop and implement data architecture solutions using technologies such as Kafka, Hadoop, Hive, PySpark, and Cloudera.
• Optimize and tune data pipelines for performance, reliability, and scalability.
• Collaborate with data scientists, analysts, and software engineers to understand data requirements and deliver actionable insights.
• Work closely with infrastructure teams to manage on-premises data infrastructure and ensure high availability and security.
• Implement best practices for data governance, data quality, and data security.
• Evaluate and recommend new technologies, tools, and frameworks to enhance data engineering capabilities.
• Provide technical leadership and mentorship to junior members of the data engineering team.

• Bachelors or masters degree in computer science, Engineering, or related field.
• 5+ years of experience in data engineering roles with a focus on building data pipelines and data infrastructure.
• Extensive hands-on experience with Kafka, Hadoop, Hive, PySpark, and Cloudera.
• Proficiency in Python programming language for data manipulation, scripting, and automation.
• Strong understanding of distributed systems, data modelling, and database concepts.
• Experience working with on-premises data infrastructure and cloud platforms (e.g., AWS, Azure, GCP).
• Streaming experience Spark streaming, Flink.
• Extensive hands-on experience on coding Java/Scala/Python
• Need to have experience on Linux/Scripting
• Strong understanding of Data Modelling
• Excellent problem-solving skills and ability to troubleshoot complex data issues.
• Strong communication and collaboration skills with the ability to work effectively in cross-functional teams.
• Proven track record of delivering high-quality solutions on time and within budget.

Expertia AI Technologies