Senior Data Engineer

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 acro