Overview
Skills
Job Details
Job Title: Data Engineer Azure Databricks & Data Factory
Key Responsibilities:
Design, develop, and maintain ETL pipelines using Azure Data Factory and Databricks for ingestion, transformation, and integration of large-scale datasets.
Build and optimize Databricks notebooks (PySpark/SparkSQL) for batch and streaming workloads.
Migrate and modernize legacy ETL workflows (e.g., SSIS, stored procedures) into scalable Databricks-based processes.
Integrate data from various sources including APIs, relational databases, and cloud data stores into Azure Data Lake and Synapse.
Implement robust data validation, monitoring, and quality checks across data layers.
Collaborate with analytics, BI, and business teams to design curated data models supporting key business use cases.
Develop and maintain metadata, data dictionaries, and lineage documentation.
Work with DevOps and Cloud teams to automate deployments and schedule data workflows.
Required Skills & Experience:
5+ years of experience in data engineering or ETL development, preferably within a cloud ecosystem.
Strong hands-on experience with:
Azure Databricks (PySpark, SparkSQL, Delta Lake)
Azure Data Factory (ADF) pipelines and orchestration
Azure Synapse / Data Lake / SQL Database
Deep understanding of data warehousing concepts, star/snowflake schemas, and performance tuning.
Experience integrating data from APIs (REST/JSON) and third-party platforms.
Solid SQL development skills with ability to write optimized queries and DDL scripts.
Familiarity with source control (Git), DevOps CI/CD pipelines, and data governance practices.
Bachelor s or Master s degree in Computer Science, Information Systems, or related field.