AWS Databrics ,ADF, Pyspark , Python , Terraform

🚀 Hiring: AWS Databricks Data Engineer

We are looking for an experienced AWS Databricks Data Engineer with strong expertise in Databricks, Azure Data Factory (ADF), PySpark, Python, Terraform, and AWS Cloud .

If you have experience building scalable cloud-based data pipelines and are looking for your next opportunity, we’d love to connect!

📌 Job Details

• Role: AWS Databricks Data Engineer
• Experience: 6–9 Years
• Locations: Indore / Pune / Hyderabad
• Notice Period: Immediate Joiners / 30 / 60 / 90 Days
• Key Skills: AWS, Databricks, ADF, PySpark, Python, Terraform

🔹 Key Responsibilities

• Design, develop, and maintain scalable data engineering solutions using Databricks .
• Develop high-performance data processing pipelines using PySpark and Python .
• Build and manage ETL/ELT workflows using Azure Data Factory (ADF) .
• Work with AWS cloud services for data storage, processing, integration, and deployment.
• Design and implement efficient data ingestion and transformation frameworks.
• Develop and maintain cloud infrastructure using Terraform / Infrastructure as Code (IaC) .
• Optimize Databricks jobs, Spark workloads, and data pipelines for performance and scalability.
• Implement data quality, monitoring, logging, and error-handling mechanisms.
• Troubleshoot production issues related to data pipelines and distributed processing.
• Collaborate with architects, analysts, DevOps teams, and business stakeholders to deliver reliable data solutions.
• Follow CI/CD, version control, security, and cloud engineering best practices.

🔹 Required Skills

• 6–9 years of experience in Data Engineering / Cloud Data Engineering .
• Strong hands-on experience with Databricks .
• Strong development experience in PySpark and Python .
• Hands-on experience with Azure Data Factory (ADF) .
• Good experience working with AWS Cloud .
• Hands-on knowledge of Terraform and Infrastructure as Code .
• Strong understanding of ETL/ELT, data pipelines, data transformation, and distributed data processing .
• Experience working with large datasets and optimizing Spark-based workloads.
• Good understanding of SQL, data modeling, and cloud data architectures.
• Strong analytical, troubleshooting, and communication skills.