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.