L2 Production Data Support Engineer

SUMMARY
About tsworks

tsworks is a leading technology innovator, providing transformative products and services designed for the digital-first world. Our mission is to provide domain expertise, innovative solutions, and thought leadership to drive exceptional user and customer experiences. Demonstrating this commitment, we have a proven track record of championing digital transformation for industries such as Banking, Travel and Hospitality, and Retail (including e-commerce and omnichannel), as well as Distribution and Supply Chain, delivering impactful solutions that drive efficiency and growth. We take pride in fostering a workplace where your skills, ideas, and attitude shape meaningful customer engagements.

About the Role

We are looking for an experienced L2 Production Data Support Engineer to oversee and maintain data workflows, troubleshoot critical issues, and ensure smooth operations of enterprise data systems. The ideal candidate should have strong analytical skills, experience with cloud-based data platforms (Azure), and the ability to work in rotational shifts.

Requirements

Location: Bengaluru
Shift: Rotational shifts, including weekends and holidays as required
Employment Type: Full - time

Key Responsibilities:

Incident Management & Monitoring:

• Monitor data pipelines, batch jobs, and real-time data processing systems.
• Perform root cause analysis (RCA) for production failures and data inconsistencies.
• Proactively identify and resolve performance bottlenecks in ETL/ELT pipelines.
• Handle escalations from L1 support and collaborate with L3 and engineering teams when required.

Data Integrity & System Maintenance:

• Perform data validation checks to ensure data quality and accuracy.
• Execute database maintenance tasks, such as indexing, partitioning, and backup validation.
• Maintain log analysis and error tracking dashboards for quick diagnosis.
• Assist in the deployment of patches and updates to improve system stability.

Automation & Process Improvement:

• Identify recurring issues and recommend automation solutions.
• Work on incident automation, log parsing, and alert tuning.
• Create and update SOPs, knowledge base articles, and runbooks for production support teams.

Collaboration & Communication:

• Act as a bridge between L1 support, developers, and cloud infrastructure teams.
• Provide timely communication on incidents, planned maintenance, and service outages.
• Participate in on-call rotations and ensure shift handovers are well - documented.

Required Skills & Experience:

Technical Skills:

• 4+ years of experience Data platform production support, monitoring, or incident management for data systems.
• Strong expertise in SQL & database management (PostgreSQL, SQL Server, MySQL, Oracle, Snowflake).
• Experience in cloud platforms (Azure) ADF, ADLS, Databricks etc.
• Power BI: Strong knowledge of Power BI service, DAX, and data modelling best practices.
• Knowledge of ETL/ELT processes and experience working with data lakes/data warehouses.
• Familiarity with incident monitoring tools like Datadog, Splunk, CloudWatch, or New Relic.
• Experience with scripting languages (Python, Shell, or PowerShell) for automation.
• Understanding of CI/CD pipelines, DevOps practices, and cloud security principles.

Soft Skills & Shift Readiness:

• Excellent communication skills able to explain technical issues to non-technical stakeholders
• Strong problem-solving mindset ability to work under pressure and handle critical incidents.
• Willingness to work in rotational shifts (including night shifts, weekends, and holidays).
• Ability to collaborate with cross-functional teams and provide effective incident resolutions.

Preferred Qualifications:

• Education: BCA / MCA / B.Tech / M.Tech in Computer Science, IT, or a related field.

• Certifications (Preferred but not mandatory):

• Microsoft Certified: Azure Fundamentals / Azure Data Engineer Associate

• PL - 300 Power BI Certification is a plus
• ITIL Foundation Certification (for incident and problem management best practices)