Solution Architect – Denodo

Location: Bangalore / Chennai / HyderabadExperience: 8+ Years

Job Overview:We are looking for an experienced Data Virtualization Engineer with strong expertise in Denodo Platform to design, develop, administer, and support data virtualization solutions. The candidate should have hands-on experience with Denodo, VQL, data sources, performance optimization, security, and integration with enterprise data platforms.

Key Responsibilities:

• Design and develop data virtualization solutions using the Denodo Platform.
• Configure and manage Denodo Virtual DataPort (VDP) environments.
• Develop and optimize views, data sources, and VQL queries.
• Integrate Denodo with databases, APIs, cloud platforms, and enterprise data sources.
• Perform performance tuning, troubleshooting, monitoring, and issue resolution.
• Manage security, authentication, access control, and data governance.
• Support Denodo upgrades, deployments, migrations, and production activities.
• Work closely with data engineers, architects, and application teams to deliver scalable data solutions.

Required Skills:Denodo Platform, Data Virtualization, Virtual DataPort (VDP), VQL, SQL, Data Integration, API Integration, Performance Tuning, Troubleshooting, Linux/Unix, Database Technologies, Security and Access Management.

Good to Have:Cloud platforms (Azure/AWS/GCP), REST APIs, ETL/ELT, Data Warehousing, Data Governance, CI/CD, and experience with Denodo administration.

Hiring: Denodo Administrator

Location: Bangalore / pune / Hyderabad💼

Experience: 7+ Years

Key Skills:

• Denodo Administration & Data Virtualization
• Linux/Unix Administration
• SQL Performance Tuning
• Oracle / SQL Server / DB2
• LDAP / AD / Kerberos / SSO
• Shell Scripting / Python
• AWS / Azure

🔹 Experience in Denodo platform administration, production support, performance tuning, security, deployment, and environment management.

Solution Architect – AZURE Data Engineering

Job Overview

We are looking for an experienced Solution Architect – Data Engineering with strong expertise in designing data solutions and hands-on experience with Azure, Synapse, PySpark, Data Warehousing, and Data Lakes. The ideal candidate should have strong architectural and data engineering knowledge.

Key Responsibilities

• Design and implement scalable data architecture and solutions.
• Develop and manage Data Warehouse and Data Lake architectures.
• Design data platforms using Medallion Architecture.
• Lead Data Engineering and ETL activities.
• Work with Azure Synapse Analytics for data processing and analytics.
• Develop data solutions using PySpark / Apache Spark.
• Define and implement data validation and data quality processes.
• Collaborate with business, data, and technology teams to deliver effective data solutions.

Required Skills

• Strong experience in Solution Architecture / Data Architecture.
• Strong knowledge of Data Warehouse and Data Lake architecture.
• Good understanding of Medallion Architecture.
• Strong experience in Data Engineering and ETL.
• Hands-on experience with Microsoft Azure and Azure Synapse Analytics.
• Strong knowledge of PySpark / Apache Spark.
• Experience with Data Validation and Data Quality.
• Good communication and stakeholder management skills.
• 
  

Experience

8+ Years

About the Role

We are looking for a Solution Architect with 10–15 years of experience to design scalable, secure, and cloud-ready solutions. The role involves working with customers, Senior Solution Architects, business analysts, project managers, and engineering teams across cloud, modernization, microservices, integration, and digital transformation initiatives.

Must Have Skills

• 10–15 years of experience in software development, architecture, and enterprise application delivery.
• Strong experience with Azure and/or AWS and cloud-native architecture.
• Hands-on experience with Microservices, REST APIs, SOA, and system integration.
• Experience in application modernization and cloud migration.
• Knowledge of Docker, Kubernetes, CI/CD, and Infrastructure as Code.
• Understanding of cloud security, IAM, networking, monitoring, and disaster recovery.
• Ability to create architecture diagrams, solution designs, and technical documentation.
• Strong analytical, communication, and customer-facing skills.

Good To Have Skills

• AWS/Azure certifications.
• Experience with Serverless, Event-Driven Architecture, Messaging, and API Management.
• Exposure to SaaS / Multi-Tenant Architecture.
• Knowledge of Generative AI and AI-enabled solutions.
• Experience with pre-sales, POCs, estimations, and technical proposals.
• Exposure to application security and compliance.
• Experience working with global customers and distributed teams.

Responsibilities

• Design end-to-end solutions and independently own defined architecture workstreams.
• Translate business and technical requirements into application, cloud, integration, and deployment designs.
• Define microservice, API, integration, and data-flow architectures.
• Guide engineering teams on architecture implementation and conduct design/code reviews.
• Contribute to cloud migration, modernization, and digital transformation initiatives.
• Participate in customer workshops, technical discussions, POCs, and solution demonstrations.
• Identify and address architectural, performance, security, and technical risks.
• Ensure solutions follow defined architecture, security, and engineering standards.
• Work closely with the Senior Solution Architect on complex and strategic engagements.
• Develop reusable architecture patterns, templates, and technical accelerators

Next

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.

Position: Technical Architect – Data Engineering

Job Summary:

• We are looking for an experienced Technical Architect to lead the design and implementation of modern cloud-based data platforms.
• The ideal candidate should have strong expertise in Azure and/or AWS, Databricks, Snowflake, modern data architecture, and large-scale data engineering.
• The candidate will work closely with business stakeholders, architects, and engineering teams to deliver scalable, secure, and high-performance data solutions.

Key Responsibilities

• Design enterprise-scale data lakehouse and data warehouse architectures.

• Define data ingestion, transformation, and serving architecture.

• Lead architecture discussions and technical governance.

• Design scalable ETL/ELT frameworks using Databricks and Snowflake.

• Define best practices for security, performance, CI/CD, and DevOps.

• Guide engineering teams on implementation.

• Collaborate with business, product, and data governance teams.

Must Have Skills :

• Azure or AWS

• Databricks

• Snowflake

• Data Lakehouse Architecture

• PySpark

• SQL

• Data Modelling

• ETL/ELT Architecture

• Performance Optimization

• CI/CD

• Terraform or Infrastructure as Code (preferred)

Preferred

• Insurance domain

• dbt

• Unity Catalog

• Delta Lake

• Iceberg

• Azure Data Factory / AWS Glue  

About the Role

We are looking for an experienced Power BI Architect to lead enterprise-wide BI initiatives. This role will be responsible for designing, implementing, and governing scalable Power BI solutions across the organization. The ideal candidate will play a key role in establishing best practices, driving adoption, and owning the overall BI architecture within the Center of Excellence (CoE).

Key Responsibilities

• Lead end-to-end implementation of Power BI solutions across the enterprise
• Design scalable, secure, and high-performance BI architecture
• Act as the Power BI Architect, providing technical leadership and direction
• Own and drive BI governance, standards, and best practices within the CoE
• Collaborate with business and technology teams to translate requirements into robust BI solutions
• Define data modeling strategies, reporting frameworks, and dashboard standards
• Ensure data accuracy, consistency, and performance optimization across reports
• Support and guide development teams in Power BI implementation
• Enable enterprise-wide adoption of Power BI through training, documentation, and mentorship
• Work closely with IT/technology teams to integrate Power BI with data platforms and enterprise systems

Required Skills & Qualifications

• 10+ years of experience in BI/Data Analytics, with strong focus on Power BI
• Proven experience in enterprise-wide Power BI implementation
• Strong expertise in:
• Power BI (Desktop, Service, Gateway, Dataflows)
• Data Modeling (Star Schema, Snowflake Schema)
• DAX, Power Query (M language)
• Experience in designing and implementing BI architecture at scale
• Strong understanding of data warehousing concepts and ETL processes
• Experience working within a Center of Excellence (CoE) model
• Excellent stakeholder management and communication skills

Preferred Skills

• Experience with Azure (Azure Synapse, Data Factory, Data Lake)
• Knowledge of DevOps practices for Power BI (CI/CD pipelines)
• Exposure to governance tools and security frameworks
• Certification in Power BI / Microsoft Data Platform

Overview:

We are looking for a Principal Architect for a Private Equity backed, fast growing AI First Product Engineering Services firm.

This role will be a key member of the core leadership team of the firm.

He/ She will serve as a strategic technical leader, solution designer, and customer advisor. In this role, you will combine deep and broad-based technical expertise with strong business acumen to architect high-value solutions, lead pre-sales engagements, and mentor our practice/CoE team. You will work closely with customers to understand their business needs, translate them into scalable technical solutions, and guide delivery teams in successful implementation.

Responsibilities:

1. Solutioning & Pre-Sales

●     Engage with customers, understand their business context, and guide them through a discovery and design process leading to a proposed solution

●     Work with sales teams to develop winning proposals, RFP responses, and technical presentations.

●     Will need to take single point ownership of the pre sales process, including client interactions, proposal preparation, presentations, pricing etc

●     Drive proof-of-concepts as part of the pre sales process

●     Build frameworks for different kinds of proposals and presentations to bring in repeatability and efficiency in the process

●     Work closely with marketing to create content around Indexnine offerings, solutions, capabilities and case studies

2. Delivery

●     Provide technical oversight during project delivery, ensuring adherence to architectural principles, standards, and best practices and ensure the as-sold solution is realised

●     Act as a trusted advisor to senior customer stakeholders (CXO level and technical leads). Will need to engage with Customers through delivery as required

●     Create points of view on accounts to help mine and grow accounts.

3. Practice & CoE Development

●     Work closely with the labs. Contribute to the development of new products/ accelerators.

●     Mentor and coach engineers to enhance their technical and customer engagement skills.

4. Thought leadership

●     Keep abreast of technology and produce points of view for Indexnine’s offerings and technical capabilities

●     Represent the company at industry forums, webinars, and client workshops.

●     Be able to independently conduct discovery and solutioning workshops with Customers

Skills/Qualifications:

●     15+ years of overall experience with a blend of architecting, pre sales and technical delivery

●     Should be leading a pre-sales unit in a services organization. Hands-on with designing solutions, proposal writing, estimation, pricing and customer presentations.

●     Broad based technical expertise and having played a Sr Architect role for at least 2 years

●     Excellent communication, stakeholder management, and team leadership skills.

●     Experience working in an IT services environment in the Product Engineering space (i.e designing and building bespoke products/solutions)

●     BE/ Masters degree

Technical Lead 

Job Description 

Role Overview 

We are seeking a highly skilled Data Engineering Lead with minimum of 5 years of hands-on experience in Azure data engineering, data warehousing, and automation-driven  integration. The ideal candidate should be a proven technical lead, capable of driving end-to-end 

project delivery and working closely with customer teams. This is a Work from Office / Customer Site role. 

Roles and Responsibilities 

• Lead the design, development, and delivery of data engineering and automation projects. 

• Architect and implement ETL/ELT pipelines using Azure Data Factory. 

• Design and manage enterprise data warehouses including dimensional modeling and 

schema optimization. 

• Manage Azure components including Storage Accounts, Data Lakes, Azure SQL, and Synapse. 

• Drive automation initiatives across data ingestion and transformation workflows. 

• Collaborate with business and technical stakeholders to translate requirements into scalable solutions. 

• Mentor team members and enforce engineering best practices. 

• Serve as the technical anchor responsible for ensuring high-quality, on-time delivery. 

Skills and Qualification 

• Strong hands-on experience with Azure Data Factory, Azure Storage, Azure SQL/Synapse. 

• Deep understanding of data warehousing concepts: star/snowflake schemas, fact/dimension modeling. 

• Experience with automation-led data engineering solutions. 

• Strong troubleshooting, optimization, and analytical skills. 

• Excellent communication and stakeholder management abilities. 

• Proven experience as a Technical Lead leading teams and delivery. 

Must Have 

• Min of 5 years of relevant data engineering experience. 

• Strong Azure Data Engineering and Data Warehousing expertise. 

• Proven Technical Lead experience. 

• Ability to work from office and customer site. 

• Strong ownership mindset with a focus on quality and delivery excellence.

Data Architect – Databricks & AWS

• Strong experience in Data Architecture, Data Engineering, Databricks, Apache Spark/PySpark, Python, and Advanced SQL.
• Design and implement scalable ETL/ELT pipelines, data platforms, and Lakehouse architectures using Medallion Architecture.
• Experience with Databricks, Databricks Workflows, Unity Catalog OR Databricks Jobs
• Strong knowledge of Delta Lake, Databricks Workflows, Delta Live Tables (DLT), and dimensional data modeling.
• Hands-on experience with AWS services such as S3, Glue, IAM, Lambda, and CloudWatch.
• Experience with Apache Airflow, Data Warehouse concepts, Git/CI-CD, performance optimization, and data quality.
• Good to have exposure to Kafka/Structured Streaming, Unity Catalog, and modern data governance.