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Senior Scalable Data Specialist
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We are seeking a seasoned Big Data Engineer with 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.
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).
About the Role:
This is an excellent opportunity for a talented Big Data Engineer to contribute to the development of scalable cloud-based data architectures and drive innovation in data processing and analysis.
