Director of Engineering, Data Platforms

Grade Level (for internal use): 13 We are seeking a strong technical and people leader to join as  Director of Engineering, Data Platforms  for our offshore team in India. In this role, you will partner closely with the core Databricks team to support the transition of existing data pipelines to the target platform, while continuing to refine, enhance, and operationalize those pipelines for scale, quality, reliability, and secure cloud-native delivery on AWS. AWS data engineering practices commonly emphasize automated and orchestrated data flows, metadata-driven pipelines, and alignment to platform guardrails and security controls.  This leader will manage a small, focused engineering team responsible for supporting offshore platform adoption and enabling asset-agnostic data onboarding into the enterprise data platform. The role is execution-oriented and collaborative in nature, with accountability for high-quality delivery, engineering rigor, and consistent partnership with global stakeholders. You will also support integrations with the enterprise data mastering platform to help ensure trusted, standardized, and reusable data flows across the ecosystem. Experience with  NeoXam DataHub  is a strong plus, particularly in environments where master, market, reference, risk, and investment data are managed across the full lifecycle—from acquisition through distribution—to create a trusted single source of truth. This role is ideal for someone who combines hands-on data platform depth with practical team leadership, strong cross-geography collaboration, and experience establishing repeatable cloud data engineering patterns across modern lakehouse and mastering ecosystems.

Data Pipeline Transition and Platform Delivery Partner with the core Databricks team to plan and execute the transition of existing data pipelines to the target data platform. Lead the offshore team in enhancing, stabilizing, and optimizing pipelines after transition, with a focus on performance, scalability, maintainability, operational excellence, and secure AWS deployment patterns. Drive implementation of repeatable engineering patterns for ingestion, transformation, testing, deployment, and monitoring across onboarded datasets. Ensure pipelines are built and managed in a way that supports long-term platform consistency, reliability, observability, and ease of support. Guide the design and operation of cloud-native data pipelines leveraging relevant AWS services such as  Amazon S3  for durable storage,  AWS Glue  for integration and catalog-driven processing, and  AWS Lake Formation  for governed data lake controls. AWS training and prescriptive guidance for data engineering emphasize building, optimizing, and securing solutions with these services. Promote the use of  AWS IAM , encryption, and environment-level controls to enforce secure access to platform resources and data products in line with enterprise governance expectations. AWS guidance highlights alignment with architectural guardrails and security controls for data engineering platforms.  Data Onboarding and Asset-Agnostic Enablement Lead a small team responsible for supporting offshore teams with onboarding data to the enterprise platform in an asset-agnostic manner. Define and operationalize onboarding patterns that can support a broad range of data assets, domains, and source systems without requiring bespoke platform redesign for each use case. Work with partner teams to simplify and standardize how data is ingested, transformed, governed, and published to the platform. Help offshore teams adopt common onboarding frameworks, technical standards, and delivery practices that improve speed and reduce friction. Establish reusable ingestion and processing patterns across batch and streaming use cases using technologies such as  AWS Glue ,  AWS Lambda ,  Amazon Kinesis , or event-driven integrations where appropriate to support scalable