Data Engineering Lead

• Data engineer with a solid technical background and banking experience in data-intensive systems (>7 years)
  
• Strong experience in Big Data, Hadoop Ecosystem, Spark Streaming, Kafka, Python, SQL, Hive, NIFI, Airflow
  
• Proficient with Azure Cloud services such as Azure Data Factory (ADF), Databricks, ADLS, Azure Synapse, Logic Apps, Azure Functions. Or similar data stack knowledge within Google/AWS cloud services
  
• Proficiency in relational SQL, Graph and NoSQL databases.
  
• Proficiency in Elastic Search and Couchbase databases
  
• In-depth skills in developing and maintaining ETL/ELT data pipelines.
  
• Experience in data modelling techniques such as Kimball star schema, 3NF, vault modelling etc.
  
• Experience in workflow management tools such as Airflow, Oozie and CI/CD tools
  
• Data streaming solution in Kafka or Confluent Kafka
  
• Hands on experience in Google Big Query, Google Analytics & Clickstream Data Model
  
• Reporting knowledge in Power Bl, Tableau, Qlik etc.
  
• Sound in Data Management Fundamentals and Data Architect, Modelling, Governance
  
• Strong Domain Knowledge in Banking/Finance area like understanding of the various processes, products, and services within the banking industry, core functions, regulations, and operational aspects of banking institutions.
  
• Hands on knowledge in Hadoop and Azure/AWS cloud ecosystem and ETL jobs migration
  
• Knowledge of Advance Analytics and Al tools

Requirements

Benefits