Data Engineer

About the Role :

We are seeking a Data Engineer to build and optimise scalable data solutions for fraud detection, reporting and machine learning. This individual contributor role focuses on real-time streaming, large-scale data processing, cloud platforms and analytics engineering.

Key Responsibilities :

- Build and maintain scalable batch and real-time data pipelines for fraud analytics.

- Develop and optimise Spark-based data processing frameworks.

- Design Kafka-based streaming and event-driven architectures.

- Implement efficient data ingestion frameworks and integrate multiple data sources.

- Build and support Snowflake data warehouse and data lake solutions.

- Develop data models for reporting, analytics, machine learning and fraud investigations.

- Design scalable cloud data solutions using AWS and/or Azure.

- Ensure data quality, governance, reliability, monitoring and compliance.

- Collaborate with Data Scientists, Fraud Analysts and Engineering teams to deliver data-driven solutions.

- Support production-grade analytics and ML platforms, ensuring reliability and performance.

Required Qualifications :

- 4+ years of experience in Data Engineering or Big Data Engineering.

- 2+ years of experience building large-scale distributed data processing systems.

- Experience supporting production-grade analytics and machine learning platforms.

- Strong hands-on experience with Apache Spark, Apache Kafka and Snowflake.

- Experience developing scalable batch and streaming data pipelines.

- Strong programming skills in Python, Scala or Java.

- Experience working with AWS and/or Azure cloud data platforms.

Tech Stack :

- Apache Spark: Large-scale distributed data processing, batch and streaming pipelines, performance tuning.

- Apache Kafka: Event streaming, real-time data processing, messaging architectures.

- Snowflake: Data warehousing, data modelling, ELT workflows, security.

- Cloud: AWS (S3, Kinesis, DynamoDB, RDS, Glue, EMR, Redshift) or Azure (ADLS, ADF, Event Hubs, Synapse, Databricks, SQL).

- Programming: Python, Scala or Java.

Preferred Skills :

- Experience in fraud analytics, fraud detection or transaction-related data processing.

- Exposure to data lakes and modern data platform architectures.

- Experience building and supporting ML data pipelines.

- Knowledge of data governance, compliance and production monitoring.

Work Location :

- Bengaluru, Karnataka

Notice Period :

- Candidates who can join within 45 days are preferred.

Skills

Data Engineering, Apache Spark, Python, AWS, Azure, Scala, Java, Kafka, Snowflake DB, Fraud Risk Implementation, ETL