Responsibilities

Design, build, and maintain scalable data pipelines to ingest, process, and transform structured and unstructured data
Develop and optimize ETL/ELT processes to ensure high data quality, consistency, and reliability
Work closely with business stakeholders, analysts, and data scientists to understand data requirements and deliver actionable datasets
Architect and manage data lakes, warehouses, and cloud-based data platforms (e.g., Azure)
Implement data models, schemas, and data integration solutions aligned with business needs
Ensure data governance, security, and compliance standards are followed across all data assets
Monitor pipeline performance and troubleshoot data-related issues to ensure system stability and uptime
Automate data workflows and enable real-time or near-real-time data processing where required
Optimize storage, compute, and processing costs while maintaining performance efficiency
Stay updated with emerging data engineering tools, technologies, and best practices to drive continuous improvement

Qualifications:

4+ years of experience in Data engineering, Databricks.
Proven knowledge of data engineering tools: SQL, Python, Spark, Databricks (Delta Lake).
Experience with SQL/NoSQL databases and Azure Data Lake Storage.
Skills in building data models, APIs, and applications using SQL, Python, and. NET.
Familiarity with Azure infrastructure, networking, and security.
Experience with data visualization tools such as Power BI, Grafana, or Tableau

Databricks Data Engineer