Data Engineer

Duration:
Full-time

Domain:
Banking

We are seeking a talented Data Engineer with Data Analyst experience to join our team, supporting projects in the banking domain for Incedo. The ideal candidate will possess hands‑on experience with the Hadoop ecosystem, including technologies such as Spark, HBase, Hive, Pig, Sqoop, Scala, Flume, HDFS, and Map Reduce. The candidate will play a key role in designing and implementing robust data pipelines and analytics solutions, supporting critical banking operations.

• Design, develop, and maintain scalable data pipelines and ETL workflows within the Hadoop ecosystem.
• Work with banking domain stakeholders to gather requirements and deliver data‑driven insights.
• Develop and optimize big data solutions using technologies such as Hadoop, Spark, and Hive.
• Perform data analysis and build dashboards to provide actionable insights for banking operations.
• Integrate various data sources, ensuring data accuracy, quality, and consistency.
• Collaborate with business analysts, data scientists, and development teams to deliver end‑to‑end solutions.
• Implement data governance and security best practices in line with regulatory compliance for the banking domain.
• Monitor and troubleshoot data workflows, ensuring system performance and reliability.
• Use tools like Sqoop and Flume to transfer and process data between structured and unstructured sources.
• Leverage HBase for real‑time data storage and querying as required by banking systems.

• Experience:
  
  10+ years of experience in data engineering and analytics, preferably in the banking/financial domain.

• Proficiency with Hadoop technologies (HDFS, Map Reduce, Hive, Pig, HBase, Sqoop, Flume).
• Expertise in Spark for distributed data processing and Scala for programming.
• Hands‑on experience with ETL/ELT workflows and data pipeline development.
• Knowledge of data storage solutions like HBase and tools for real‑time data ingestion and processing.