Senior Data Engineer | 4 To 6 Years| Job

We are seeking a talented and experienced Data Engineer to join our growing team. As a Data Engineer, you will be responsible for designing, developing, and maintaining our data architecture and infrastructure. You will collaborate closely with cross-functional teams to gather requirements, build scalable data pipelines, and ensure the reliability and efficiency of our data systems. The ideal candidate will have a strong background in data engineering, experience with big data technologies, and a passion for driving actionable insights from complex datasets.

What you will do:
Design, develop, and maintain scalable data pipelines and ETL processes to support data analytics and machine learning initiatives.
Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and implement solutions to address business needs.
Optimize and tune existing data infrastructure to improve performance, reliability, and scalability.
Implement data quality and monitoring processes to ensure the integrity and accuracy of our data assets.
Stay current with emerging technologies and best practices in data engineering and contribute to the continuous improvement of our data infrastructure.
Provide technical guidance and mentorship to junior team members.

Who you are:
Bachelor's degree or higher in Computer Science, Engineering, or a related field.
4-6 years of experience in data engineering with a focus on building data pipelines and data infrastructure.
Proficiency in programming languages such as Java, Python, or Scala.
Strong SQL skills and experience with relational databases (e.g., MySQL, PostgreSQL).
Experience with big data technologies such as Hadoop, Spark, or Kafka.
Proficiency in Linux and scripting capabilities.
Familiarity with cloud platforms such as Azure, or Google Cloud Platform.
Excellent problem-solving skills and attention to detail.
Strong communication and collaboration skills.

Information above is Internshala's interpretation and paraphrasing of what we found on the shared link.