Fractal
AzureDigiops
Neural analysis suggests this role is
optimal for Mid candidates.
“Azure Digiops at Fractal. Skills: Azure Databricks, Azure Data Factory, PySpark. Monitor data pipelines. Troubleshoot data pipelines”
What You'll Achieve.
Ensure minimal downtime; Cost-efficiency; Minimize manual intervention; Knowledge sharing; Proactive monitoring; SLA compliance
Industry & Context.
Troubleshoot issues; Root cause analysis
What They're Looking For.
Must Have
Azure Databricks, Azure Data Factory, Databricks, Data Engineering, Data Lake, Delta lake, PySpark, Python, Spark, SQL
Nice to Have
GenAI, Agentic AI
What You'll Do.
Monitor data pipelines
Troubleshoot data pipelines
Perform root cause analysis
Enhance ADF pipelines
Optimize ADF pipelines
Fine-tune PySpark code
Implement automation solutions
Provide technical solutions
How You'll Work.
Team & Collaboration
Collaborate with L1 support teams; Work closely with stakeholders
Full Job Description
It's fun to work in a company where people truly BELIEVE in what they are doing! _We 're committed to bringing passion and customer focus to the business._ Job Description **About Fractal** What makes Fractal a GREAT fit for you? When you join Fractal, you’ll be part of a fast-growing team that helps our clients leverage AI together with the power of behavioural sciences to make better decisions. We’re a strategic analytics partner to most admired fortune 500 companies globally, we help them power every human decision in the enterprise by bringing analytics, AI and behavioural science to the decision. Our people enjoy a collaborative work environment, exceptional training and career development — as well as unlimited growth opportunities. We have a Glassdoor rating of 4 / 5 and achieve customer NPS of 9/ 10. If you like working with a curious, supportive, high-performing team, Fractal is the place for you. Job Description Job Description **Locations-** Pune, Mumbai, Gurgaon, Noida, Chennai, Coimbatore, Bangalore **Experience** \- 4.5-6 years **Responsibilities:** 1\. Monitor, troubleshoot, and resolve issues related to data pipelines, ETL workflows, and jobs in Azure Data Factory and Azure Databricks. 2\. Perform root cause analysis (RCA) on incidents and implement sustainable fixes to ensure minimal downtime. 3\. Collaborate with L1 support teams for incident escalation and resolution. 4\. Enhance and optimize existing ADF pipelines and Databricks notebooks for performance and cost-efficiency. Fine-tune PySpark code 5\. Review and update pipeline configurations to align with business and technical requirements. 6\. Assist in developing new features or pipelines to integrate with existing solutions based on evolving requirements. 7\. Write modular, reusable, and well-documented PySpark and Python code for data processing. 8\. Implement automation solutions to minimize manual intervention in repetitive tasks. 9\. Work closely with stakeholders to gather requirements
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