Job Description

Lead Associate - Data Architect

Department: IT

Employment Type: Permanent - Full Time

Location: Pune

The Data Architect plays a critical role in shaping, designing, and evolving Davies’ data platform across our suite of SaaS products. They are responsible for architecting scalable, sustainable, and secure data solutions that underpin both our internal analytics needs and our application microservices. This role leads the development of our data strategy, defining data‑centric architectural approaches, establishing a unified data ontology, and overseeing key capabilities including data ingestion, integration, migration, modelling, laking, and reporting.
The Data Architect also provides oversight for BI and reporting processes, ensuring the business has timely access to high‑quality insights. Acting as a senior technical authority, the Data Architect ensures that data solutions comply with regulatory and contractual requirements—including data retention, security, anonymisation, and segregation—while championing long‑term, high‑quality engineering approaches over tactical workarounds. They represent the function at senior management level and play a key role in mentoring and supporting BI and data engineering professionals to ensure development standards are understood and adhered to.

Key Responsibilities

Data Architecture & Strategy

• Lead the data strategy for the design, development, and delivery of data‑driven software solutions.
• Provide architectural leadership on the adoption and implementation of data‑centric system design. Define and maintain a central enterprise data ontology to support consistent, scalable data practices across products.
• Oversee architectural approaches to data ingestion, migration, integration, laking, modelling, and reporting.

Governance, Compliance & Quality

• Design data solutions that comply with regulatory and contractual obligations including retention, anonymisation, segregation, lineage, and data security.
• Establish development frameworks and standards for data engineering, modelling, metadata, and data quality.
• Ensure solutions are scalable, resilient, and aligned to long‑term business and technical strategy.

Platform Design & Technical Leadership

• Architect the data platform required to support application microservices and SaaS product needs.
• Lead the strategy and delivery of data warehousing and analytical platform capabilities.
• Drive research and evaluation of emerging data technologies aligned with our technical roadmap.
• Provide oversight and guidance to data engineering and BI teams, ensuring best‑practice approaches.

Business Intelligence & Insights

• Design and implement processes for BI and analytics delivery—including test‑driven reporting development and automated data pipelines.
• Identify intelligence and reporting needs across the business, working with BI teams to translate requirements into scalable solutions.
• Ensure the timely and accurate provision of reporting and dashboards for clients and internal stakeholders.
• Report on the performance and effectiveness of the BI function to senior management.

Collaboration & Leadership

• Lead cross‑functional collaboration with product, engineering, architecture, and data teams to ensure data solutions support business objectives.
• Represent the data function at senior management level.
• Mentor and supervise BI and data professionals, promoting continuous development and high‑quality standards.

Skills, Knowledge and Expertise

• Strong leadership experience and ability to act as a role model for technical and professional standards.
• Experience designing data‑centric system architectures including ontologies, modelling, and platform strategy.
• Hands‑on expertise with SQL, NoSQL, and Graph database technologies.
• Experience delivering cloud‑first data solutions using Azure or AWS.
• Strong analytical and problem‑solving skills
• Excellent communication skills—clear, concise, and confident at senior levels
• Experience mentoring or supervising BI/data professionals.
• Deep understanding of data governance, quality, integration, and regulatory compliance.