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Open nowPosted 36 days ago

Platform Engineer

TechBlocks58 open roles

Where
Hyderabad
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Your applicationOpen nowPlatform EngineerTechBlocks · Hyderabad
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This job: posted 36 days ago

The posting

Role Overview

We are seeking an experienced Platform Engineer with strong expertise in enterprise SaaS analytics platform administration, data integration, APIs, SQL, Git, and Azure DevOps.

The candidate will be responsible for administering and supporting enterprise analytics platforms, integrating data from engineering and DevOps systems, and ensuring the reliability, accessibility, and usability of platform data. A key requirement is the ability to take ownership of an existing platform with limited or undocumented knowledge, understand its architecture and data flows, and establish effective operational processes and documentation.

The ideal candidate should be comfortable working independently, troubleshooting complex platform and integration issues, and collaborating with engineering, DevOps, security, and business stakeholders.

Key Responsibilities

Enterprise SaaS Platform Administration

  • Administer and support enterprise SaaS-based analytics platforms in a large-scale organizational environment. Configure and maintain platform settings, users, access, data sources, integrations, and analytics capabilities. Monitor platform health, availability, data quality, and integration status. Troubleshoot platform, data, configuration, and integration-related issues. Establish operational procedures and best practices for ongoing platform administration. Take ownership of an existing platform and quickly develop an understanding of its architecture, configuration, integrations, and operational dependencies.

Git & Azure DevOps Data Integration

  • Work with Git and Azure DevOps data models to understand engineering and software delivery data. Configure and maintain integrations that ingest engineering and DevOps data into enterprise analytics platforms. Understand repository, commit, pull request, branch, build, release, work item, and related engineering data structures. Validate data ingestion, transformation, mapping, and availability within the analytics platform. Troubleshoot data discrepancies and integration failures across source systems and the analytics platform.

API Integration & Data Engineering

  • Design, implement, and maintain API-based integrations between enterprise SaaS platforms and internal systems. Work with REST APIs and associated authentication mechanisms to retrieve, exchange, and manage platform data. Develop scripts or utilities to automate data extraction, validation, platform administration, and operational activities. Monitor API integrations and troubleshoot failures, authentication issues, data mapping problems, and connectivity issues. Collaborate with engineering teams to understand source-system changes and their impact on downstream analytics.

SQL & Data Validation

  • Develop and execute SQL queries for data validation, troubleshooting, reconciliation, and analysis. Investigate data quality issues and identify discrepancies between source systems and analytics platforms. Validate data completeness, accuracy, consistency, and timeliness. Support reporting and analytics teams by ensuring reliable underlying platform data. Develop queries and validation mechanisms to support platform monitoring and operational reporting.

Platform Takeover & Documentation

  • Take ownership of an existing platform with limited, incomplete, or undocumented operational knowledge. Reverse-engineer platform configurations, integrations, data flows, dependencies, and operational processes. Assess the existing environment and identify gaps in documentation, governance, monitoring, and support processes. Create and maintain comprehensive technical and operational documentation. Establish knowledge-transfer and support procedures to ensure sustainable platform ownership. Identify opportunities to improve platform reliability, automation, maintainability, and operational efficiency.

Stakeholder & Cross-functional Collaboration

  • Collaborate with Engineering, DevOps, Data, Security, and business stakeholders to understand platform requirements and priorities. Work with source-system owners to resolve data and integration issues. Communicate platform health, issues, risks, dependencies, and planned changes to relevant stakeholders. Support enterprise initiatives involving engineering analytics, software delivery metrics, and platform modernization.

Required Skills & Experience

  • 5+ years of experience in Platform Engineering, SaaS Platform Administration, Application Administration, Data Engineering, or a related technical role. Strong experience administering enterprise SaaS analytics platforms. Hands-on experience working with Git and Azure DevOps data models. Strong understanding of engineering and DevOps data and how it is captured, structured, and consumed for analytics. Hands-on experience with API integration, preferably REST APIs. Strong SQL skills for data analysis, validation, reconciliation, and troubleshooting. Experience integrating enterprise applications and SaaS platforms with internal and external systems. Demonstrated experience taking ownership of an existing, undocumented or poorly documented platform and establishing operational knowledge and documentation. Strong troubleshooting and problem-solving skills across application, data, API, and integration layers. Ability to work independently and take ownership of platform operations and technical issues. Strong communication skills and ability to work with technical and non-technical stakeholders.

Strongly Preferred Skills

  • Hands-on experience with BlueOptima or Bloomfilter. Exposure to Software Engineering Intelligence (SEI) or engineering productivity analytics platforms. Experience with process mining and process analytics. Experience administering enterprise SSO integrations. Experience with SCIM-based user provisioning and lifecycle management. Experience with enterprise access administration, RBAC, and user entitlement management. Exposure to engineering productivity metrics and software delivery analytics. Experience working with large-scale enterprise DevOps environments.
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