Senior Data Engineer

Kroll; New Delhi; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Kroll is seeking a Senior Data Engineer to design, build, and govern enterprise data platforms that enable secure, scalable analytics and AI initiatives across the organization. You will blend architecture with hands‑on engineering, partnering with security, governance, BI, and product teams to establish enterprise standards.

Responsibilities include designing data architecture for lakehouses, data lakes, and data warehouses; developing ETL/ELT pipelines; implementing IaC, CI/CD; and driving

Qualifications

• Bachelor’s degree in CS/IS/Engineering required.
• 5+ years in Data Engineering, Data Architecture, or related fields.
• Experience designing cloud data platforms with Lakehouse/Data Mesh concepts.

Responsibilities

• Design enterprise data architecture aligned with business strategy.
• Develop scalable ETL/ELT pipelines for structured and semi-structured data.
• Implement infrastructure automation (IaC) and CI/CD practices.
• Drive data governance, quality, and security across cloud environments.
• Lead architecture reviews and mentor engineers.

Skills

Leadership

Stakeholder management

Architectural thinking

Cloud computing

Databricks

Azure

Python

SQL

ETL/ELT

Education

Bachelor's degree in Computer Science / Information Systems / Engineering

Tools

Databricks

Microsoft Fabric

Snowflake

Azure Synapse Analytics

Azure Data Lake Storage

Job description

Job Description

We are seeking a Senior Data Engineer responsible for designing, implementing, and governing enterprise data platforms that enable secure, scalable, and high-quality data solutions across the organization. This role combines strategic architecture with hands‑on engineering, ensuring that data platforms support analytics, AI, operational reporting, regulatory compliance, and business transformation initiatives. The ideal candidate partners closely with business stakeholders, data engineers, application teams, security, and governance functions to build modern cloud‑native data ecosystems while establishing enterprise standards for architecture, data quality, governance, security, and platform operations.

Key Responsibilities

Enterprise Data Architecture

• Design and maintain enterprise data architecture that aligns with business strategy and technology roadmaps.
• Define logical, conceptual, and physical data models across operational and analytical platforms.
• Develop scalable architecture patterns for data lakes, data warehouses, lakehouses, and modern analytics platforms.
• Establish standards for metadata, lineage, master data, reference data, and data lifecycle management.
• Drive technology evaluations and architectural decisions for cloud-based data platforms.

Data Platform Engineering

• Design, build, and optimize enterprise data platforms using cloud-native technologies.
• Develop and maintain scalable ETL/ELT pipelines for structured and semi-structured data.
• Implement infrastructure automation and deployment pipelines using Infrastructure as Code and CI/CD practices.
• Optimize platform performance, reliability, scalability, and cost across cloud environments.
• Troubleshoot platform issues and continuously improve operational resilience.

Data Governance & Security

• Design and implement enterprise data governance frameworks.
• Lead initiatives involving confidential data identification, classification, masking, tokenization, encryption, and access control.
• Define and implement data retention, auditing, and compliance standards.
• Collaborate with Security, Risk, Legal, and Compliance teams to ensure adherence to regulatory requirements.
• Establish enterprise metadata management and data lineage capabilities.

Data Quality & Reliability

• Develop enterprise data quality frameworks including validation, reconciliation, completeness, accuracy, and monitoring.
• Implement automated quality controls within ingestion and transformation pipelines.
• Define KPIs and metrics to measure platform health and data quality.
• Lead initiatives that improve trust in enterprise data assets.

Cloud Platform Administration

• Administer enterprise analytics platforms including Databricks, Microsoft Fabric, Snowflake, Azure and AWS environments
• Manage workspace provisioning, Unity Catalog governance, compute optimization, storage management, and platform security.
• Implement role‑based access controls and least‑privilege security models.
• Monitor platform utilization, capacity planning, and cost optimization.

Analytics Enablement

• Partner with BI teams to enable trusted enterprise reporting.
• Support semantic models, reporting platforms, and self-service analytics capabilities.
• Ensure data products are discoverable, reusable, and governed.

Architecture Leadership

• Lead architecture reviews and technical design sessions.
• Provide technical leadership to engineering teams and mentor junior architects and engineers.
• Define enterprise best practices, standards, and reusable design patterns.
• Review solution designs for scalability, maintainability, security, and performance.

Operational Excellence

• Improve platform reliability through monitoring, automation, observability, and incident response.
• Develop operational runbooks and disaster recovery strategies.
• Drive continuous improvement initiatives across platform operations.
• Support production deployments and release management.

Cross‑Functional Collaboration

• Partner with Finance, HR, Operations, Product, Security, and Engineering teams to understand business requirements.
• Translate business objectives into scalable technical solutions.
• Communicate architecture decisions and technical strategy to both technical and executive audiences.
• Lead cross-functional initiatives involving multiple business units and external vendors.

Requirements

• Bachelor's degree in Computer Science/ Information Systems/Engineering, or related field.
• 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 modern data architecture principles including Lakehouse, Data Mesh, and Data Fabric concepts.
• Experience implementing enterprise data governance and security frameworks.
• Proven ability to lead large-scale technical initiatives from design through production.

Technical Skills

• Cloud Platforms: Microsoft Azure (Preferred), AWS
• Data Platforms: Databricks (Required), Microsoft Fabric, Snowflake, Azure Synapse Analytics, Azure Data Lake Storage
• Databases: SQL Server, Oracle, PostgreSQL, Azure SQL, Delta Lake
• Data Engineering: Spark, PySpark, SQL, Python, ETL/ELT pipeline development, Streaming and batch processing
• Governance & Metadata: Microsoft Purview, Unity Catalog, Data Catalogs, Data Lineage, Data Classification, Data Masking, Data Quality Frameworks
• DevOps & Automation: Git, Azure DevOps, GitHub Actions, Terraform, ARM/Bicep, CI/CD Pipelines
• Reporting & Analytics: Power BI, Semantic Models, DAX, Data Modeling

About Kroll

In a world of disruption and increasingly complex business challenges, our professionals bring truth into focus with the Kroll Lens. Our sharp analytical skills, paired with the latest technology, allow us to give our clients clarity - not just answers - in all areas of business. We value the diverse backgrounds and perspectives that enable us to think globally. As part of One team, One Kroll, you’ll contribute to a supportive and collaborative work environment that empowers you to excel.

Kroll is the premier global valuation and corporate finance advisor with expertise in complex valuation, disputes and investigations, M&A, restructuring, and compliance and regulatory consulting. Our professionals balance analytical skills, deep market insight and independence to help our clients make sound decisions. As an organization, we think globally—and encourage our people to do the same.

Kroll is committed to equal opportunity and diversity, and recruits people based on merit.