How much salary can I expect as a Senior Data Reliability Engineer in Infosys in Bengaluru/Bangalore?

You can expect a minimum salary of 0 INR. The salary offered will depend on your skills, experience and performance in the interview.

What is the eligibility criteria to apply for Senior Data Reliability Engineer in Infosys in Bengaluru/Bangalore?

The candidate should have completed the required education and people who have 9 to 14 years are eligible to apply for this job. You can apply for more jobs in Bengaluru/Bangalore to get hired quickly.

Is there any specific skill required for this job?

The candidate should have sound communication skills and sound communication skills for this job.

Who can apply for this job?

Both Male and Female candidates can apply for this job.

Is it a work from home job?

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No work-related deposit needs to be made during your employment with the company.

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Senior Data Reliability Engineer

Infosys

Senior Data Reliability Engineer

Infosys

Bengaluru/Bangalore

Not disclosed

Work from Office

Full Time

Min. 9 years

Job Description

Sr. Data Reliability Engineer

9+ years of experience in Data Engineering, Data Platform, SRE, or Reliability roles Strong experience applying SRE principles to data systems Hands-on experience with enterprise data platforms such as: Snowflake, BigQuery, Redshift, Synapse Data lakes (ADLS, S3, GCS) Expertise with data orchestration and ETL tools: Airflow, ADF, dbt, Informatica, or similar Strong SQL and deep data debugging skills Experience with monitoring and observability tools: Prometheus, Grafana, Datadog, CloudWatch, Azure Monitor Strong scripting skills (Python, Shell) Deep knowledge of Linux/Unix systems Strong analytical, troubleshooting, and leadership skills Excellent communication and stakeholder management abilities Data Platform Reliability & Stability Own end-to-end reliability, availability, and performance of enterprise data platforms Define and track SLAs, SLOs, and SLIs for data pipelines and platforms Proactively reduce data downtime, failures, and data quality incidents Design systems for fault tolerance, scalability, and resilience