Data Engineer

Build and maintain reliable, scalable data pipelines and data products primarily using Databricks and AWS services.

Implement and ensure data ingestion, validation, transformation, and quality assurance adhering to privacy and compliance standards.

Maintain pipeline health through monitoring, alerting, and support while collaborating with senior engineers and business users to deliver dependable data products.

Hands-on experience building and maintaining data pipelines and products with Databricks, PySpark, Spark SQL, and Delta Lake or similar lakehouse platforms.

Proficiency in AWS data and serverless services including Lambda, Glue, S3, Kinesis, SNS/SQS.

Good Python and SQL skills; understanding of data modelling and data quality fundamentals.

Degree in computer science or related field, or equivalent knowledge and experience; Work Experience Required: Not explicitly mentioned in the JD; No travel required; Hybrid work model.

Experience or strong interest in working with modern data engineering tools and cloud platforms, especially Databricks and AWS.

Ability to follow good engineering and data practices including CI/CD and infrastructure as code.

Comfortable working under guidance of senior engineers and engaging with cross-functional teams to translate needs into data solutions.