Data Architect Lead

Role Purpose

Own the end-to-end data architecture strategy for the organization, leading the design of scalable,

secure, and high-performing data platforms. Act as the technical authority on data modeling,

integration, governance, and infrastructure, while leading a team of data architects/engineers and

guiding cross-functional stakeholders on data-driven initiatives.

Key Responsibilities

• Architecture & Strategy

• Define and own the enterprise data architecture strategy, standards, and roadmap, aligned with business objectives.

• Design scalable data models (conceptual, logical, physical) across OLTP, OLAP, and data lake/lakehouse environments.

• Architect data pipelines, ETL/ELT processes, and integration patterns across source systems, data warehouses and downstream applications.

• Evaluate and select appropriate data platforms, tools, and technologies (cloud data warehouses, lakehouses, streaming platforms).

• Define and enforce data governance, data quality, master data management (MDM), and metadata management frameworks.

• Technical Leadership

• Lead and mentor a team of data architects, data engineers and/or analysts.

• Review and approve data architecture designs, data models, and technical solutions proposed by the team.

• Set technical direction on data security, privacy, access control, and compliance (e.g. GDPR, data residency requirements).

• Drive adoption of best practices in data modeling, naming conventions, version control, and documentation.

• Delivery & Collaboration

• Partner with business stakeholders, product owners, and engineering teams to translate business requirements into data architecture solutions.

• Collaborate with BI/Analytics, Data Science, and application teams to ensure data is structured for reporting, analytics and AI/ML use cases.

• Oversee data migration strategies, including legacy system decommissioning and cloud migration projects.

• Support integration projects, ensuring consistent and reliable data flow across systems (ERP, CRM, third-party applications).

• Participate in architecture review boards and provide technical sign-off on major data initiatives.

• Governance & Quality

• Establish data quality standards, monitoring, and remediation processes.

• Define and maintain data catalogs, data lineage, and metadata repositories.

• Ensure architecture decisions support scalability, performance, security, and cost optimization.

Requirements

Requirements

• 8-10 years of experience in data architecture, data engineering, or related roles, with at least 3-5 years in a lead/architect capacity.

• Strong hands-on experience designing data models (dimensional modeling, star/snowflake schemas, normalized/denormalized models).

• Deep expertise in at least one major cloud data platform (AWS Redshift/Glue, Azure Synapse/Data Factory, GCP BigQuery/Dataflow, Snowflake, Databricks).

• Strong SQL skills and experience with ETL/ELT tools (Informatica, Talend, dbt, Azure Data Factory, etc.).

• Experience with data warehousing, data lakes, and/or lakehouse architectures.

• Solid understanding of data governance, MDM, data quality, and metadata management principles.

• Experience with API-based and event-driven integration (Kafka, REST, OIC, etc.).

• Strong stakeholder management and ability to translate business needs into technical architecture.

• Experience leading and mentoring technical teams. Desirable

• Experience with BI/reporting tools (Power BI, Tableau, OBIEE, Looker).

• Familiarity with AI/ML data pipeline requirements and feature stores.

• Experience with data security/compliance frameworks (GDPR, HIPAA, data residency).

• Relevant certifications (AWS/Azure/GCP Data Architect, Snowflake, Databricks, DAMA/CDMP).

• Experience in a specific industry vertical relevant to the hiring organization (Finance, Healthcare, Government, Retail).

• Programming experience in Python or Scala for data engineering tasks.

• Key Competencies

• Strategic thinking, strong technical depth combined with business acumen, leadership and

• mentoring ability, structured problem solving, clear communication with both technical and non

• technical stakeholders.