4 months ago
Hyderābād, IndiaSenior
Responsibilities
- Design and maintain enterprise data architecture aligned with business strategy and technology roadmaps.
- Define logical, conceptual, and physical data models across operational and analytical platforms.
- Develop scalable architectures for data lakes, data warehouses, lakehouses, and analytics platforms.
- Build, maintain, and optimize cloud-native data platforms and scalable ETL/ELT pipelines.
- Implement infrastructure automation, deployment pipelines, and platform performance, reliability, scalability, and cost improvements.
- Design and implement enterprise data governance, metadata management, lineage, retention, auditing, compliance, and security frameworks.
- Implement confidential-data identification, classification, masking, tokenization, encryption, access control, and least-privilege security models.
- Develop data quality frameworks and automated validation, reconciliation, completeness, accuracy, monitoring, and platform-health controls.
- Administer Databricks, Microsoft Fabric, Snowflake, Azure, and AWS environments, including workspace provisioning, Unity Catalog governance, compute optimization, storage management, and capacity planning.
- Partner with BI teams to support semantic models, reporting platforms, self-service analytics, and discoverable and governed data products.
- Lead architecture reviews, technical design sessions, technical initiatives, solution reviews, and cross-functional programs involving business units and vendors.
- Improve platform operations through monitoring, automation, observability, incident response, runbooks, disaster recovery, production deployments, and release management.
- Provide technical leadership and mentorship to junior architects and engineers.
Requirements
- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
- At least 5 years of experience in Data Engineering, Data Architecture, Platform Engineering, or related disciplines.
- Extensive experience designing enterprise-scale cloud data platforms.
- Strong understanding of Lakehouse, Data Mesh, and Data Fabric architecture concepts.
- Experience implementing enterprise data governance and security frameworks.
- Proven ability to lead large-scale technical initiatives from design through production.
- Databricks experience is required; Microsoft Azure experience is preferred.
- Experience with cloud data platforms, data modeling, ETL/ELT pipeline development, streaming and batch processing, governance, metadata, data lineage, data classification, data masking, and data quality frameworks.
- Experience with DevOps and automation tools including Git, Azure DevOps, GitHub Actions, Terraform, ARM/Bicep, and CI/CD pipelines.
- Experience supporting reporting and analytics with Power BI, semantic models, DAX, and data modeling.
Benefits
- Hybrid work arrangement, as indicated by the posting's #LI-Hybrid designation.
- Supportive and collaborative work environment with opportunities to contribute across global business functions.
- Kroll is committed to equal opportunity and diversity and recruits based on merit.
Tech Stack
Apache SparkAWSAzureDatabricksGitGitHub ActionsMicrosoft SQL ServerPostgreSQLPythonSnowflakeSQLTerraform
Categories
Data Engineering
About Kroll
Kroll provides risk and financial advisory services, including valuation, corporate finance, restructuring, investigations, cyber risk, and compliance, to enterprises, financial institutions and law firms. It earns fees for advisory, due diligence, disputes, and agency/trustee services across global capital markets. Founded in 1972 and headquartered in New York, the firm operates internationally and is known for complex valuations and forensic investigations.