Experience
17 - 21 yrs
Job Location
Hyderabad, India
Vacancy
1
Designation
Director Data Science
Job Type
Not specified
Job Description
Your key responsibilities:
- Enterprise Data Architecture Leadership: Define and evolve enterprise data architecture strategy, frameworks, standards, operating models, and ownership of data catalog, lineage, and metadata aligned with business and IT goals.
- Domain Data Architecture: Act as domain architect across key business areas, designing business-aligned data models, semantic layers, KPIs, and reusable data products while driving data maturity and MDM adoption.
- Data Platform & Integration: Architect scalable, resilient data platforms and ingestion pipelines (batch/streaming) using Kafka, Informatica, Databricks, APIs, and cloud-native services to meet SLAs for availability, quality, and performance.
- Governance, Security & DevOps: Establish data governance, security, and compliance standards; implement CI/CD, Infrastructure as Code, and DataOps practices to ensure quality, consistency, and secure delivery of data products.
- Cost Optimization & FinOps: Drive cloud FinOps best practices by designing cost-efficient data pipelines and platforms, monitoring usage, and optimizing resource consumption through serverless and reserved capacity models.
- Innovation & Stakeholder Enablement: Enable advanced analytics and AI/ML use cases, lead innovation pilots and PoCs, provide architectural oversight, and mentor teams while partnering closely with business and technology stakeholders.
You bring:
- Cloud Data Architecture & Mesh: Design and lead a decentralized Cloud Data Mesh on AWS, integrating legacy enterprise systems (e.g., SAP S/4HANA, BW/4HANA) with cloud-native data platforms such as Databricks and Informatica.
- Data Governance, Security & MDM: Implement robust governance, security, and metadata frameworks using Databricks Unity Catalog, AWS IAM, and Informatica MDM to enable access control, privacy, lineage, discovery, and trusted master data.
- End-to-End Data Lifecycle Expertise: Demonstrate deep expertise across the full data lifecycle from ingestion (SAP ingestion tools, low-code/no-code), transformation (Spark), to consumption via APIs and analytics platforms.
- Integration, Streaming & Platforms: Architect scalable batch and streaming data pipelines and enterprise integration patterns for complex ecosystems including SAP, CRM platforms, and modern data platforms (Databricks, Informatica; Palantir preferred).
- DataOps, DevOps & Cloud Enablement: Drive architectural adoption through DataOps practices, CI/CD pipelines, Infrastructure-as-Code (Terraform), and cloud-native DevOps to ensure automation, scalability, and agility on AWS.
- Leadership & Experience: Bring 17+ years of enterprise data architecture and domain modeling experience, strong stakeholder leadership and communication skills, and a Bachelor s/Master s degree in Computer Science, Data Engineering, or a related field.
We bring:
- Lead enterprise-wide data transformation initiatives to modernize and optimize data strategy and operations.
- Drive adoption of data-driven decision-making and influence strategic business and IT initiatives.
- Promote data innovation by identifying and implementing emerging technologies and advanced analytics solutions.
- Collaborate with global teams to design scalable, high-performance data platforms and architectures.
- Establish best practices for data governance, quality, and integration across the enterprise.
- Mentor and enable teams, fostering a culture of continuous improvement and data excellence.
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