5 Data architecture Jobs in Delhi, NCR and Gurgaon | Data architecture Job openings in Delhi, NCR and Gurgaon

IMMEDIATE JOINERS ONLY

Key Responsibilities:

1                   Data Flow Mapping & Lineage

2                   Design and produce end-to-end data flow maps for critical data items – from market source/core systems, through Data Lake staging, zone 2 and consumption zone 3, to downstream reporting, dashboards and analytics use cases.

3                   Document data lineage and transformations for critical data elements identified in the Master Data Requirements exercise, ensuring traceability that is audit-defensible and supports regulatory, governance and AI-readiness needs.

4                   Map data availability by country/Data Lake against the Product Hierarchy (to profit-centre level), building the consolidated Commercial Data Landscape view of what exists, where it sits (source only, staging, or consumption) and what is not captured at all.

5                   Document cross-system dependencies and cross-border data flows, flagging data residency, privacy and regulatory considerations to the appropriate governance forums.

6                   Data Inventory, Data Model Alignment & Gap Analysis

•                    Own and mature the data asset inventory, catalogue and data dictionary aligned to the consolidated Master Data Requirements Template – resolving “Not Specified”, “TBD” and “validation required” availability statuses through structured validation with Market IT and Data Engineering.

•                    Align business data requirements to the conceptual and logical data model of the target Data Lakehouse, ensuring the dependency between data model design and lineage tracking of critical data items is explicitly documented.

•                    Perform gap and hydration analysis by market and product, quantifying the scale of data that must be brought into the Data Lakes and providing sizing input to the Data Foundation Lead, DAE architects and Data Engineering delivery plans.

•                    Contribute to the Data Consolidation Plan towards a single source of truth, including recommended sequencing based on business priority (Top 200 fields, Horizon 1–3 priorities).

•                    Stakeholder Engagement & Workshops

•                    Work hand-in-hand with the Data Foundation Lead, Data & Analytics Programme Manager, Data Engineers, DAE/infrastructure architects, Local Market IT and Business stakeholders (Regional and Market) as the connective tissue between business data needs and technical implementation.

•                    Plan and facilitate structured interviews and cross-functional validation workshops with business, technology and data stakeholders to corroborate actual operating data flows against documented processes – establishing a fact-based, evidence-backed view rather than relying on documentation alone.

•                    Translate ambiguous business asks into clear data definitions, mapping rules and acceptance criteria that Data Engineering can build against, and play back findings to senior stakeholders in clear, visual, decision-oriented formats.

•                    Manage competing priorities across multiple markets with tact, keeping momentum in an environment of constrained capacity and differing local system landscapes.

•                    Governance, Ownership & Documentation

•                    Produce and maintain the Data Ownership & Accountability Matrix – mapping data owners, stewards and custodians per data asset and highlighting ownership gaps for remediation.

•                    Classify data assets by sensitivity and business function, aligning to Data Protection Policy, PDPA and applicable regulatory expectations (e.g. MAS guidelines) in partnership with Risk & Compliance.

•                    Ensure all data flow maps, lineage records and inventory artefacts are version-controlled, audit-ready and handed over cleanly into BAU data governance processes.

•                    Produce source to Datalake mapping document and data catalogue for missing data elements to complete Datalake hydration

Key Skills

•                    Data flow mapping and lineage documentation – proven ability to draw clear, accurate source-to-consumption data flow maps across complex multi-system, multi-market landscapes.

•                    Data architecture and modelling – strong grasp of conceptual/logical data models, data lake/lakehouse zone architectures (staging, conformed, consumption), data marts and MDM concepts.

•                    Data inventory, catalogue, dictionary and metadata management; familiarity with lineage/catalogue tooling (e.g. Purview, Collibra) and diagramming tools (e.g. Visio, ErWin, Lucidchart).

•                    Hands-on data profiling and validation skills (SQL essential) to verify what actually exists in source systems and lake zones.

•                    Strong stakeholder management – this is critical: able to build trust and drive outcomes across regional leadership, market business teams, Market IT and engineering, and to facilitate effective cross-functional workshops.

•                    Insurance domain knowledge – ideally commercial and specialty lines, with an understanding of policy, claims, reinsurance and underwriting data.

•                    Data quality, governance and privacy concepts, including cross-border data considerations.

•                    Clear written and visual communication – able to make complex data landscapes understandable to executives.

Experience & Qualification Requirements:

•                    8+ years’ experience in data architecture, data business analysis or information architecture roles, with at least:

•                    3+ years documenting data flows, lineage or data landscapes across multi-system / multi-market environments.

•                    Experience in Insurance or Financial Services, ideally within data foundation, data lake or data governance programmes.

•                    Demonstrated delivery of data inventory / data mapping / current-state data landscape assessments involving both business and IT stakeholders.

•                    Relevant certification (e.g. DAMA CDMP, TOGAF, cloud data platform certifications) preferred.

MANDATORY:

• Super Quality Data Architect, Data Engineering Manager / Director Profile
• Must have 12+ YOE in Data Engineering roles, with at least 2+ years in a Leadership role
• Must have 7+ YOE in hands-on Tech development with Java (Highly preferred) or Python, Node.JS, GoLang
• Must have strong experience in large data technologies, tools like HDFS, YARN, Map-Reduce, Hive, Kafka, Spark, Airflow, Presto etc.
• Strong expertise in HLD and LLD, to design scalable, maintainable data architectures.
• Must have managed a team of at least 5+ Data Engineers (Read Leadership role in CV)
• Product Companies (Prefers high-scale, data-heavy companies)

PREFERRED:

• Must be from Tier - 1 Colleges, preferred IIT
• Candidates must have spent a minimum 3 yrs in each company.
• Must have recent 4+ YOE with high-growth Product startups, and should have implemented Data Engineering systems from an early stage in the Company

ROLES & RESPONSIBILITIES:

• Lead and mentor a team of data engineers, ensuring high performance and career growth.
• Architect and optimize scalable data infrastructure, ensuring high availability and reliability.
• Drive the development and implementation of data governance frameworks and best practices.
• Work closely with cross-functional teams to define and execute a data roadmap.
• Optimize data processing workflows for performance and cost efficiency.
• Ensure data security, compliance, and quality across all data platforms.
• Foster a culture of innovation and technical excellence within the data team.

IDEAL CANDIDATE:

• 10+ years of experience in software/data engineering, with at least 3+ years in a leadership role.
• Expertise in backend development with programming languages such as Java, PHP, Python, Node.JS, GoLang, JavaScript, HTML, and CSS.
• Proficiency in SQL, Python, and Scala for data processing and analytics.
• Strong understanding of cloud platforms (AWS, GCP, or Azure) and their data services.
• Strong foundation and expertise in HLD and LLD, as well as design patterns, preferably using Spring Boot or Google Guice
• Experience in big data technologies such as Spark, Hadoop, Kafka, and distributed computing frameworks.
• Hands-on experience with data warehousing solutions such as Snowflake, Redshift, or BigQuery
• Deep knowledge of data governance, security, and compliance (GDPR, SOC2, etc.).
• Experience in NoSQL databases like Redis, Cassandra, MongoDB, and TiDB.
• Familiarity with automation and DevOps tools like Jenkins, Ansible, Docker, Kubernetes, Chef, Grafana, and ELK.
• Proven ability to drive technical strategy and align it with business objectives.
• Strong leadership, communication, and stakeholder management skills.

PREFERRED QUALIFICATIONS:

• Experience in machine learning infrastructure or MLOps is a plus.
• Exposure to real-time data processing and analytics.
• Interest in data structures, algorithm analysis and design, multicore programming, and scalable architecture.
• Prior experience in a SaaS or high-growth tech company.

Digital and Technology Architecture

• Head the digital transformation and innovation projects from idea generation to new ventures in close collaboration with business stakeholders and external partners
• Present the vision & value of proposed architectures and solutions to a wide range of audiences in alignment with business priorities and objectives
• Plans tasks and estimates for the required research and volume of activities to complete work
• Own and assess non-functional requirements and propose solutions for Availability, Backup, Capacity, Performance, Redundancy, Reliability, Scalability, Supportability, Risks and Costs models
• Provide strategic guidance to teams on managing third-party service providers in terms of service levels, costing, etc.
• Drive the team to ensure appropriate documentation is developed in support of value realization
• Lead the technical team and head collaboration between Business Users and software providers to build digital solutions

Enterprise Architecture

• Ownership of overall Enterprise Architecture including compliances and standards
• Head the overall Architecture blueprint and roadmap for  applications aligning with Enterprise Architecture
• Identify important potential technologies and approaches to address current and future Enterprise needs, evaluating their applicability and fit, as well as leading the definition of standards and best practice for their use

Data Architecture

• Ownership of overall Data Architecture including compliances and standards
• Head the overall Architecture blueprint and roadmap applications aligning with Data Architecture
• Identify important potential technologies and approaches to address current and future Data needs, evaluating their applicability and fit, as well as leading the definition of standards and best practice for their use