Job Title : Big Data Engineer - Scala
Experience : 7 to 10Years (Minimum 3+ years in Scala)
Notice Period : Immediate to 30 Days
Role Overview :
We are looking for a highly skilled Big Data Engineer (Scala) with strong expertise in Scala, Spark, Python, NiFi, and Apache Kafka to join our data engineering team. The ideal candidate will have a proven track record in building, scaling, and optimizing big data pipelines, and hands-on experience in distributed data systems and cloud-based solutions.
Key Responsibilities :
- Design, develop, and optimize large-scale data pipelines and distributed data processing systems.
- Work extensively with Scala, Spark (PySpark), and Python for data processing and transformation.
- Develop and integrate streaming solutions using Apache Kafka and orchestration tools like NiFi / Airflow.
- Write efficient queries and perform data analysis using Jupyter Notebooks and SQL.
- Collaborate with cross-functional teams to design scalable cloud-based data architectures.
- Ensure delivery of high-quality code through code reviews, performance tuning, and best practices.
- Build monitoring and alerting systems leveraging Splunk or equivalent tools.
- Participate in CI / CD workflows using Git, Jenkins, and other DevOps tools.
- Contribute to product development with a focus on scalability, maintainability, and performance.
Mandatory Skills :
Scala - Minimum 3+ years of hands-on experience.Strong expertise in Spark (PySpark) and Python.Hands-on experience with Apache Kafka.Knowledge of NiFi / Airflow for orchestration.Strong experience in Distributed Data Systems (5+ years).Proficiency in SQL and query optimization.Good understanding of Cloud Architecture.Preferred Skills :
Exposure to messaging technologies like Apache Kafka or equivalent.Experience in designing intuitive, responsive UIs for data analytics visualization.Familiarity with Splunk or other monitoring / alerting solutions.Hands-on experience with CI / CD tools (Git, Jenkins).Strong grasp of software engineering concepts, data modeling, and optimization techniques(ref : hirist.tech)