Senior Data Engineer - Databricks

We are looking for a skilled Databricks Developer to design, develop, and optimize big data solutions using Apache Spark and Databricks on Azure cloud. The ideal candidate will have strong experience in data engineering, ETL pipelines, and performance optimization.

Key Responsibilities:

Design, develop, and optimize ETL pipelines in Databricks.
Build data ingestion, transformation, and processing workflows using Apache Spark.
Work with structured and unstructured data from various sources.
Optimize Spark jobs for performance, cost efficiency, and scalability.
Implement CI/CD for Databricks workflows and manage version control.
Work closely with Data Engineers, Data Scientists, and Business Analysts to support analytics and reporting.
Implement security best practices andmanage access controls in Databricks.
Troubleshoot performance and scalability issues in big data processing.

Required Skills:

Strong hands-on experience with Databricks and Apache Spark (PySpark/Scala/Java).
Proficiency in SQL for data analysis and transformation.
Experience in cloud platforms (Azure, AWS,or GCP), especially Azure Data Lake, AWS S3, or GCP Big Query.
Hands-on experience with ETL tools, Data Pipelines, and Data Warehousing.
Strong knowledge of CI/CD, Git, and Dev Opstools for data workflows.
Knowledge of Delta Lake, Lakehouse architecture, and performance tuning.
Experience in handling large-scale datasets and distributed computing.

Preferred

Skills:

Experience with Databricks MLflow and machine learning pipelines.
Knowledge of Kafka, Airflow, or Snowflake.
Understanding of data governance,compliance, and security policies.

Education & Experience:

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
Experience in Databricks development