Qualitest

AI-powered software testing and quality engineering

Senior Data Technical Lead

Data Engineering +1Confirmed live in the last 24 hours

Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

At least 10 years of experience in data engineering, including at least 5 years in a senior technical lead role with direct accountability for architecture quality and delivery outcomes.
Strong hands-on experience with Microsoft Azure and Microsoft Fabric data platforms, including Azure Databricks, Azure Data Factory, data lake patterns, SQL, Python, ETL/ELT design, orchestration, monitoring, and production support.
Ability to lead by example through solution design, prototyping, implementation support, code review, architecture review, defect triage, and technical problem solving.
Experience with enterprise governance, security, and supportability requirements, including access control, auditability, deployment discipline, documentation, and operational readiness.
Experience working in complex enterprise environments with multiple stakeholders, distributed delivery teams, and external suppliers.
Bachelor's degree in computer science, information systems, engineering, or a related field, or equivalent practical experience.
Strong technical judgment and ability to translate business needs into practical, supportable solution designs.
Troubleshooting, root-cause analysis, and performance optimization capability across reporting and data platforms.
Communication and stakeholder management skills, including the ability to challenge constructively and drive technical decisions.
Delivery discipline, including planning, estimation, risk management, and quality control in enterprise environments.
Experience with Microsoft Azure and Microsoft Fabric data platform services, primarily Azure Databricks, Azure Data Factory, Azure Data Lake, SQL, Python, and related orchestration, monitoring, and engineering capabilities.
Experience with version control and delivery tooling such as Git and Azure DevOps, and CI/CD practices for analytics and data solutions.
Experience with Power BI Desktop and Power BI Service, SQL, and Python, including DAX, Power Query, semantic models, workspace governance, deployment, automation, and performance optimization.
Knowledge of governance and security practices relevant to Microsoft enterprise environments, including identity, access control, data protection, and operational support.

Responsibilities

Own end-to-end technical delivery for analytics and data solutions, from solution shaping and design through implementation, deployment, and production support.
Provide hands-on technical leadership in Power BI and Azure data engineering through prototyping, architecture reviews, code reviews, troubleshooting, performance optimization, and implementation guidance.
Translate business requirements into practical technical solutions, define implementation approaches, validate estimates and dependencies, and actively manage delivery risk.
Establish and enforce engineering standards for semantic models, reporting, data pipelines, testing, deployment, monitoring, documentation, and support readiness.
Ensure solutions meet enterprise expectations for security, access control, data governance, quality, compliance, scalability, and maintainability.
Guide and challenge delivery teams and suppliers, identify technical debt and quality issues early, and drive remediation to achieve reliable delivery outcomes.

Desired Qualifications

Experience in regulated industries such as life sciences, healthcare, or other compliance-heavy environments.
Expert-level hands-on experience with Power BI, SQL, and Python, including semantic modeling, DAX, Power Query, data analysis, automation, workspace and dataset governance, row-level security, deployment, and performance tuning.
Hands-on experience with Microsoft Fabric, Azure AI services, or analytics modernization initiatives in a Microsoft-first ecosystem.
Relevant Microsoft certifications in Power BI, Azure Data Engineering, Azure Architecture, or Fabric.
Experience supporting supplier screening, technical interviews, or quality assurance of vendor-delivered work.

PositionRole title: Senior Data Technical LeadSeniority: Senior technical lead / solution delivery leadRole purposeThis role leads the technical delivery of enterprise analytics and data solutions in a Microsoft first & Databricks environment. The position is accountable for turning business requirements into scalable, secure, supportable solutions across Databricks and Azure-based data platforms, while setting a high engineering bar through direct hands-on contribution.The successful candidate will lead by example through solution design, prototyping, code and architecture reviews, technical troubleshooting, delivery guidance, and enforcement of engineering, governance, security, and operational standards across internal and supplier delivery teams.Key Responsibilities• Own end-to-end technical delivery for analytics and data solutions, from solution shaping and design through implementation, deployment, and production support.• Provide strong hands-on leadership in Power BI and Azure data engineering, including prototyping, architecture reviews, code reviews, troubleshooting, performance optimization, and implementation guidance.• Translate business requirements into practical technical solutions, define implementation approaches, validate estimates and dependencies, and actively manage delivery risk.• Establish and enforce engineering standards for semantic models, reporting, data pipelines, testing, deployment, monitoring, documentation, and support readiness.• Ensure solutions meet enterprise expectations for security, access control, data governance, quality, compliance, scalability, and maintainability.• Guide and challenge delivery teams and suppliers, identify technical debt and quality issues early, and drive remediation to achieve reliable delivery outcomes.Must Have• 10+ years of experience in data, engineering, including 5+ years in a senior technical lead role with direct accountability for architecture quality and delivery outcomes.• Strong hands-on experience with Microsoft Azure and Microsoft Fabric data platforms, including Azure Databricks, Azure Data Factory, data lake patterns, SQL, Python, ETL/ELT design, orchestration, monitoring, and production support.• Proven ability to lead by example through solution design, prototyping, implementation support, code review, architecture review, defect triage, and technical problem solving.• Strong experience with enterprise governance, security, and supportability requirements, including access control, auditability, deployment discipline, documentation, and operational readiness.• Experience working in complex enterprise environments with multiple stakeholders, distributed delivery teams, and external suppliers.• Bachelor's degree in computer science, Information Systems, Engineering, or a related field, or equivalent practical experience.Nice to Have• Experience in regulated industries such as life sciences, healthcare, or other compliance-heavy environments.• Expert-level hands-on experience with Power BI, SQL, and Python, including semantic modeling, DAX, Power Query, data analysis, automation, workspace and dataset governance, row-level security, deployment, and performance tuning.• Hands-on experience with Microsoft Fabric, Azure AI services, or analytics modernization initiatives in a Microsoft-first ecosystem.• Relevant Microsoft certifications in Power BI, Azure Data Engineering, Azure Architecture, or Fabric.• Experience supporting supplier screening, technical interviews, or quality assurance of vendor-delivered work.Key Skills• Strong technical judgment and the ability to turn business needs into practical, supportable solution designs.• Excellent troubleshooting, root-cause analysis, and performance optimization capability across reporting and data platforms.• Strong communication and stakeholder management skills, with the ability to challenge constructively and drive technical decisions.• Delivery discipline, including planning, estimation, risk management, and quality control in enterprise environments.Core Technology Stack• Microsoft Azure and Microsoft Fabric data platform services, primarily Azure Databricks, Azure Data Factory, Azure Data Lake, SQL, Python, and related orchestration, monitoring, and engineering capabilities.• Version control and delivery tooling such as Git, Azure DevOps, and CI/CD practice for analytics and data solutions.• Power BI Desktop and Power BI Service, together with SQL and Python, including DAX, Power Query, semantic models, workspace governance, deployment, automation, and performance optimization.• Governance and security practices relevant to Microsoft enterprise environments, including identity, access control, data protection, and operational support.

About the Company

Qualitest

AI-powered software testing and quality engineering

Qualitest provides software testing services powered by AI to help clients in healthcare, finance, and technology improve quality and speed up time to market. Its core product is Qualisense, an AI tool that enhances risk-based testing by prioritizing testing efforts, identifying high-risk areas, and optimizing test coverage. This allows Qualitest to automate and accelerate testing workflows, reduce costs, and improve operational efficiency for large, diverse enterprises worldwide. The company differentiates itself from competitors through its focus on AI-driven testing and risk-based strategies, enabling faster release cycles and better customer experiences. Qualitest aims to help organizations deliver reliable software quickly and at lower overall risk by combining specialized testing services with advanced AI-enabled tooling, primarily under long-term service contracts and partnerships.

Company size: 1,001-5,000
Company stage: Acquired
Total funding: $497M
Headquarters: Fairfield, CT
Founded: 1997

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