Database Engineer

About the role

We are looking for a Database Engineer to design, build, and maintain scalable data pipelines that support both batch and real‑time processing. You will work closely with data architects and analysts to deliver reliable, high‑performance datasets for downstream consumption.

Key responsibilities

• Develop and maintain scalable data pipelines for batch and streaming workloads.
• Build robust ingestion frameworks using APIs, file‑based sources, and streaming platforms such as Kafka or Kinesis.
• Design Python and PySpark transformation logic for large‑scale datasets.
• Create Python‑based microservices and REST APIs for secure data access.
• Integrate pipelines with Databricks, Delta Lake, Snowflake, and serverless services like AWS Lambda or Azure Functions.
• Optimize jobs for performance, cost efficiency, and query tuning.
• Ensure data quality, validation, and monitoring across all pipelines.
• Collaborate on lakehouse implementation following medallion architecture.
• Automate deployment using CI/CD and orchestration tools.

Required profile

• 2–4 years of hands‑on data engineering experience.
• Strong programming skills in Python and PySpark.
• Solid SQL expertise for data transformation and analysis.
• Experience building production‑grade ETL/ELT pipelines.
• Familiarity with APIs, microservices, and data‑as‑a‑service concepts.

Required skills

• Python
• PySpark
• SQL
• Apache Spark
• Databricks
• Delta Lake
• Snowflake
• AWS Lambda
• Azure Functions
• Kafka
• Kinesis
• AWS Glue
• dbt
• REST APIs
• CI/CD pipelines