Dfs Tower Lead

Tata Consultancy Services; Irvine (CA); Presencial; USD 120.000 - 150.000; Tempo integral

Resumo da vaga

Tata Consultancy Services Limited is seeking an experienced L3 Production Support Engineer to provide advanced support for enterprise data platforms and critical pipelines. The role emphasizes AWS, Databricks, Airflow, Dremio, Python and SQL with a strong focus on incident management, RCA, stability, and continuous service improvement.

Responsibilities include monitoring workloads on AWS services, troubleshooting incidents, performing RCA, and supporting data quality and metadata validation.

Qualificações

• Experience supporting enterprise data platforms and critical data pipelines.
• Strong expertise in AWS, Databricks, Airflow, Dremio, Python, SQL and data quality frameworks.
• Proven incident management and Root Cause Analysis (RCA) skills; focus on stability and improvements.

Responsabilidades

• Provide L3 production support for enterprise data platforms and ensure high availability of critical pipelines.
• Monitor data workloads on AWS (S3, Athena, CloudWatch), Databricks, and Dremio environments.
• Troubleshoot and resolve complex production incidents within SLAs and minimize business impact.
• Perform detailed RCA for recurring issues and implement permanent corrective actions.
• Analyze, debug, and optimize ETL/ELT workflows orchestrated through Airflow.
• Support and maintain Databricks clusters, jobs, notebooks, and runtime configurations.
• Develop and execute SQL and Python scripts for investigation and validation.
• Monitor health using CloudWatch and identify performance bottlenecks and anomalies.
• Manage data residing in AWS S3 and queried via Athena, ensuring reliability and performance.
• Perform data profiling and metadata validation to align with requirements.
• Implement data quality checks, reconciliation processes, and validation frameworks.
• Support schema changes, column additions, and data model enhancements with downtime minimization.
• Execute and validate regression testing during deployments and infrastructure upgrades.
• Manage Databricks runtime upgrades and environment patching.
• Use GitHub for source control, release tracking, and deployment support.
• Collaborate with Data Engineering, Architecture, Business and Infra teams to improve stability.
• Participate in on-call rotations and support incidents during off-hours.

Conhecimentos

AWS

S3

Athena

CloudWatch

Airflow

Databricks

Dremio

Python

SQL

GitHub

Metadata

Profiling

Schema

Data quality checks

Regression testing

Runtime upgrades

RCA fixes

Ferramentas

Databricks

Dremio

Airflow

Descrição da vaga

AWS, S3, Athena, CloudWatch, Airflow, Databricks, Dremio, Python, SQL, GitHub, metadata, profiling, schema, data quality checks, regression testing, runtime upgrades and RCA fixes

We are seeking an experienced L3 Production Support Engineer to provide advanced support for enterprise data platforms and critical data pipelines. The role requires expertise in AWS, Databricks, Airflow, Dremio, Python, SQL, and data quality frameworks, with a strong focus on incident management, RCA, platform stability, runtime upgrades, and continuous service improvement.

Key Responsibilities

• 1.Provide L3 production support for enterprise data platforms and ensure high availability of business-critical data pipelines.
• 2.Monitor and support data workloads running on AWS services (S3, Athena, CloudWatch), Databricks, and Dremio environments.
• 3.Troubleshoot and resolve complex production incidents, ensuring compliance with defined SLAs and minimizing business impact.
• 4.Perform detailed Root Cause Analysis (RCA) for recurring issues and implement permanent corrective actions.
• 5.Analyze, debug, and optimize ETL/ELT workflows orchestrated through Apache Airflow.
• 6.Support and maintain Databricks clusters, jobs, notebooks, workflows, and runtime configurations.
• 7.Develop and execute SQL and Python scripts for issue investigation, data validation, and operational support activities.
• 8.Monitor infrastructure and application health using AWS CloudWatch, identifying performance bottlenecks and system anomalies.
• 9.Manage and support data residing in AWS S3 and queried through Athena, ensuring reliability and performance.
• 10.Perform data profiling and metadata validation to ensure alignment with business and technical requirements.
• 11.Implement and monitor data quality checks, reconciliation processes, and validation frameworks to maintain data integrity.
• 12.Support schema changes, column additions, and data model enhancements while ensuring downstream application compatibility.
• 13.Execute and validate regression testing during code deployments, platform changes, and infrastructure upgrades.
• 14.Manage Databricks runtime upgrades, platform patching, and environment maintenance activities with minimal downtime.
• 15.Utilize GitHub for source code management, version control, release tracking, and deployment support.
• 16.Work closely with Data Engineering, Architecture, Business, and Infrastructure teams to resolve production issues and improve platform stability.
• 17.Participate in on-call rotations and provide support for critical incidents during off-hours and planned maintenance windows.
• 18.Develop operational runbooks, knowledge art icles, and support documentation to improve support efficiency.