Data architect

Trianz is a leading-edge technology platforms and services company that accelerates digital transformations at Fortune100 and emerging companies worldwide in data & analytics, digital experiences, cloud infrastructure, and security.

The company’s “IP Led Transformations” vision, strategy, and business model are based on insightsfrom a recent global studyspanning 20+ industries and 5000+ companies worldwide.

Trianz believesthat companies around the world face three challenges in their digital transformation journeys - shrinking‘time to transform’ due to competition & AI, lack of digital-ready talent, and uncertain economicconditions.

To help clients leapfrog over these challenges, Trianz has built IP and platforms that have transformed the adoption of the cloud, data, analytics & insights AI.

Specifically, the following Trianzplatforms are changingthe way companies approach transformations in various disciplines: Concierto: A fully automated platform to Migrate, Manage, and Maximize the multi & hybrid cloud.

A zero code and Saa S platform, Concierto allows teams to migrateto AWS, Azureand GCP and manage them efficiently from a single pane ofglass.

Visit for more information.

Avrio is a Data to AI Saa S platform designed to drive data-led transformation at lightning speed.

Through conversational AI, organizations seamlessly engage with all their data, unlocking real-time insights, and uncovering hidden opportunities and risks—all within one powerfulplatform.

Visit to know more.

Pulse: Recognizing that workforces will be distributed, mobile, and fluid, Trianz has built a ‘future of work’ digital workplace platform called Pulse.

Visit Since the market launch of this strategyin mid-2023, Trianz has experienced enormous growth, success and recognition.

Some of Trianz’ built IP in data and analytics was acquired by Amazon.

Since then, Trianz has been made an engineering partner of Amazon for building/supporting connected ecosystems across multiple AWS platforms.

Trianz Concierto cloud platform and Extrica Datamesh are gaining traction, winning over 2 dozen customers with 50+ customers and partners in the queue.

As an AWS Premier level qualified partner, Trianz is building and delivering platforms and services that are disrupting industry value propositions.

At a time when the servicesindustry is struggling with its abilityto deliver value at a pace that Trianz demand, Trianz “IP Led Services”business model and value proposition are changing the game for companies as well as cloud providers such as AWS, Azure and GCP.

Rated #1 by clients in value delivery 5 years in a row, Trianz will surpassindustry growth rates by a wide margin in the coming years with its “IP Led Digital Transformations” model.

Trianz is led by Sri Manchalaa former specialforces officer from the Indianarmy and authorn digital leadership(( Crossing the Digital Faultline | Trianz ) and a team of veteransfrom well known firms such as Deloitte, HCL, KPMG, Wipro and conglomerates such as GE.

Given its above industrygrowth and demands, Trianz has recently raised private equity capital to scale the companyover the next several years ( Trianz Announces Strategic Growth Capital Investment by Capital Square Partners (prnewswire.com) ).

Trianz is seekingto bolster its senior and mid-level leadership with top talent across GTM, Engineering, Servicesand Partnership organizations.

We are seeking talent that is driven by our purpose- to help accelerate digital transformations- and is motivated to change the way our industry delivers value.

Job Responsibilities Architectural Design : Architect secure, scalable, highly performant data engineering and management solutions, including data warehouses, data lake, ELT / ETL and real-time data engineering / pipeline solutions.

Support Principal Data Architect in defining and maintaining Practice reference data engineering and data management architectures.

Databricks Implementation: Design and manage scalable end-to-end data solutions leveraging native Databricks capabilities including Data Engineering – Delta Live Tables, Apache Spark, Structured Streaming, Notebooks, Git CI/CD, Databricks’ supported file types, Libraries.

Data Warehousing – Databricks SQL, best practice data modeling.

Delta Lake – Delta Lake + Delta Live tables, incremental and streaming workloads, table history, file management, API utilization.

Databricks Data Unity Catalog – access control, lineage, Delta Sharing, identity management.

Hyperscaler Design: Competently leverage data-related cloud platform (AWS or Azure or GCP) capabilities to architect and develop end-to-end data engineering and data management solutions.

Client Engagement: Regular collaboration and partnership with clients to understand their challenges and needs then translate requirements into data solutions that drive customer value.

Support proposal development.

Data Modeling: Create and maintain conceptual, logical, and physical data models that support both transactional and analytical needs.

Ensure data models are optimized for performance and scalability.

Creativity: Be an out-of-the-box thinker and passionate about applying your skills to new and existing solutions alike while always demonstrating a customer-first mentality.

12+ years hands-on data solution architecture and implementation experience on modern cloud platforms (AWS preferred) including microservice and event-driven architectures.

Databricks Professional Data Engineer certification.

Databricks Platform Architect accreditation (AWS or Azure).

Databricks Platform Administrator accreditation.

Hands-on experience with Databricks Lakehouse implementations, Delta Live Tables and building scalable data pipelines including real-time (Kafka, Kinesis) in addition to Databricks’ Structured Streaming.

Demonstrated, holistic experience and competence with Databricks concepts including Delta tables, Apache Spark, Structured Streaming, Notebooks, Git CI/CD, Libraries Databricks SQL.

An architectural certification on either AWS, Azure or GCP.

Experience with ML orchestration tools such as MLflow and Kubeflow.

Containerization proficiency (Docker, Kubernetes) to deploy data pipelines and models.

Practical experience with end-to-end data engineering and data management supporting functions including data modeling (conceptual, logical & physical), BI & analytics, data governance, data quality, data security / privacy / compliance, IAM, performance optimization.

Advanced SQL and data profiling.

Python or Scala.

Strong communication skills with the ability to convey technical concepts to non-technical users.

Strong, self-management skills demonstrating ability to multitask and self-manage goals and activities.

Additional / Nice-to-have Qualifications Databricks ML Engineer certification (Associate or Professional) Databricks Generative AI Engineer certification Databricks Apache Spark Developer certification Any additional Databricks accreditations or certifications If interested kindly share your updated resume with the below details to Kumar.venkatappa@trianz.com CTC - ECTC - NP - Prefered location