Architect – Data Engineer

Allianz

. Rapidly assess and understand the current enterprise data platform across all layers and components .

Posted 9/15/2026full-timePune • IndiaSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in Data Architecture and Engineering, with a focus on enterprise-scale data platforms, including Lakehouse/Medallion principles. Proficient in Azure Data Platform technologies and architectural best practices, ensuring scalability, security, and performance optimization.

Highest-signal resume keywords

Data ArchitectureAzure Data PlatformData GovernanceInfrastructure as CodeData Modelling

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Hard Skills

Data EngineeringData ArchitectureData ModellingETL/ELT FrameworksPythonSQLAzure Synapse AnalyticsAzure DatabricksDelta LakeTerraform

Soft Skills

CommunicationStakeholder ManagementTechnical Leadership

Tools & Technologies

Azure PurviewPower BIOracle GoldenGateDockerKubernetesCI/CDAzure DevOpsEvent HubKafkaKinesis

Industry Keywords

Enterprise Data PlatformLakehouse PrinciplesData QualityData LineageRegulated Environments

Tech Stack

Tools & technologies

AzureCloudDockerETLKafkaKubernetesOraclePythonSparkSQLTerraformUnity

About the role

Key responsibilities & impact

Rapidly assess and understand the current enterprise data platform across all layers and components
Define and own the target-state architecture
Drive scalability, availability, performance, security and resilience requirements into platform design
Design the architectural roadmap for the next stage of platform transformation
Translate business and data requirements into architectural decisions, reference designs and technical standards
Provide hands-on architectural guidance to engineering teams during delivery
Evaluate and select technologies, tools and vendors using trade-off analysis
Champion automation, self-service and infrastructure-as-code
Identify architectural risks, dependencies and trade-offs and recommend mitigation strategies
Define integration patterns, data flows and governance standards across ingestion, transformation and consumption layers
Establish and enforce architecture principles, design patterns and platform standards
Collaborate with data governance, business, information security, enterprise architecture and technology stakeholders
Support migration planning through target architectures, transition states and validation strategies
Drive decisions on platform tooling, infrastructure and service selection
Provide technical leadership through architecture reviews, code reviews, mentoring and implementation governance
Define agentic integration patterns to enhance data ingestion options

Requirements

What you’ll need

10+ years of experience in Data Engineering and/or Data Architecture
At least 4–5 years in a solution or platform architect role
Proven experience joining mid-flight programs and understanding existing implementations
Track record of delivering architecture across complex, multi-layer data platforms in enterprise environments
Experience working in regulated or enterprise-scale environments
Enterprise-scale data platform architecture using Lakehouse/Medallion principles
Expertise in data modelling, data governance, data quality, lineage, CDC, SCD, audit and control frameworks
Experience with Unity Catalog and Azure Purview
Experience architecting batch and real-time data processing, ETL/ELT frameworks, migration strategies and performance optimization
Hands-on Azure Data Platform experience, including Azure Synapse Analytics, ADLS Gen2, Delta Lake, Azure Analysis Services, Oracle GoldenGate or equivalent, and Power BI semantic models
Extensive Azure Databricks experience, including Delta Lake, Delta Live Tables, Unity Catalog, Spark, workflow orchestration, governance and Lakehouse migration
Strong Azure cloud architecture expertise covering security, networking, scalability, resilience and cost optimization
Experience with Infrastructure as Code, Terraform preferred, CI/CD, Azure DevOps/GitHub Actions and Docker/Kubernetes
Advanced Python and SQL skills
Experience with environment management, monitoring and alerting, vulnerability management, and incident/problem management
Experience establishing testing frameworks including unit testing, data reconciliation, smoke testing and end-to-end validation
Strong communication and stakeholder management skills
Nice to have: exposure to Event Hub, Kafka or Kinesis
Nice to have: familiarity with MLOps
Nice to have: experience with monitoring and observability frameworks such as Dynatrace

Benefits

Comp & perks

Inclusive workplace grounded in integrity, fairness, inclusion and trust
Equal-opportunity workplace
Employee support focused on ambitions, dreams and challenges