Databricks - Data Engineering

Mandatory Skills: Databricks, Spark, Python / SQL

Responsibilities

Design, develop, and optimize data workflows and notebooks using Databricks to ingest, transform, and load data from various sources into the data lake.

Build and maintain scalable and efficient data processing workflows using Spark (PySpark or Spark SQL) by following coding standards and best practices.

Collaborate with technical and business stakeholders to understand data requirements and translate them into technical solutions.

Develop data models and schemas to support reporting and analytics needs.

Ensure data quality, integrity, and security by implementing appropriate checks and controls.

Monitor and optimize data processing performance, identifying, and resolving bottlenecks.

Stay up to date with the latest advancements in data engineering and Databricks technologies.

Qualifications

2-6 years of experience in designing, implementing, and maintaining data solutions on Databricks

Experience with Azure cloud platform

Experience with ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes

Knowledge of data warehousing and data modelling concepts

Experience with Python or SQL

Understanding of DevOps principles and practices

Excellent problem-solving and troubleshooting skills

Strong communication and teamwork skills