Data Engineer

Data Bricks Engineer – Banking

5–8 years of experience designing and building data pipelines using Apache Spark, Databricks or equivalent bigdata frameworks.

• Hands on expertise with streaming and messaging systems such as
  
  

Apache Kafka (publish subscribe architecture), Confluent Cloud,

RabbitMQ or Azure Event Hub. Experience creating producers,

consumers and topics and integrating them into downstream

processing.

• Deep understanding of relational databases and CDC. Proficiency
  
  

in SQL Server, Oracle or other RDBMSs; experience capturing

change events using Debezium or native CDC tools and

transforming them for downstream consumption.

• Proficiency in programming languages such as Python, Scala or
  
  

Java and solid knowledge of SQL for data manipulation and

transformation.

• Cloud platform expertise. Experience with Azure or AWS services for
  
  

data storage, compute and orchestration (e.g., ADLS, S3, Azure

Data Factory, AWS Glue, Airflow, DBX, DLT).

• Data modelling and warehousing. Knowledge of data Lakehouse
  
  

architectures, Delta Lake, partitioning strategies and performance

optimisation.

• Version control and DevOps. Familiarity with Git and CI/CD
  
  

pipelines; ability to automate deployment and manage

infrastructure as code.

• Strong problem solving and communication skills. Ability to work
  
  

with cross functional teams and articulate complex technical

concepts to nontechnical stakeholders.

Preferred/ Bonus Skills

• Experience with event driven architectures and micro services
  
  

integration.

• Exposure to NiFi, Flume or other ingestion frameworks for
  
  

connecting heterogeneous sources.

• Knowledge of graph processing or machine learning pipelines on
  
  

Spark.

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