Data Platform Engineer

Data Platform Engineer

About The Company :

ARA’s client TechGlobal (pseudonym) is a global leader in strategy, technology consulting and digital services, enabling clients in more than 100+ countries to implement cutting edge solutions in their transformation journey. TechGlobal helps businesses become digital-first and digital-ready. The company has a global presence with 600000+ employees ( 200000+ in India). India is a focus for them with their Development Centres presence in over 10 locations across Tier 1 and Tier 2 cities. They are recognised for their people first and employee oriented policies. Along with offering hybrid work options, a Pan India presence gives flexible location options to employees.

Project Role Description :

Assists with the data platform blueprint and design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models.

Must have skills :

Databricks Unified Data Analytics Platform

AI Experience is Mandatory

Minimum

12

year(s) of experience is required

PAN India Location

Summary :

As a Data Platform Engineer, you will assist with the data platform blueprint and design, encompassing the relevant data platform components. Your typical day will involve collaborating with Integration Architects and Data Architects to ensure cohesive integration between systems and data models, while also engaging in discussions to refine and enhance the overall data architecture strategy. You will be involved in various stages of the data platform lifecycle, ensuring that all components work harmoniously to support the organization's data needs and objectives.

Responsibilities :

• Design and build complex pipelines using Delta Lake, Auto Loader, Delta Live Tables (DLT), and deployment using Asset Bundles.
• AI Experience is Mandatory
• Proven experience as a Data Architect and Data Engineer leading enterprise-scale Lakehouse initiatives.
• Expert-level understanding of modern Data & Analytics Architecture patterns including Data Mesh, Data Products, and Lakehouse Architecture.
• Excellent programming and debugging skills in Python.
• Strong experience with PySpark for building scalable and modular ETL / ELT pipelines.
• Architect data ingestion and transformation using DLT Expectations, modular Databricks Functions, and reusable pipeline components.
• Must have hands-on expertise in at least one major cloud platform : AWS, GCP, or Azure.
• Lead implementation of Unity Catalog : create catalogs, schemas, role-based access policies, lineage visibility, and data classification tagging (PII, PHI, etc.).
• Guide organization-wide governance via Unity Catalog setup : workspace linkage, SSO, audit logging, external locations, and Volume access.
• Enable cross-platform data access using Lakehouse Federation, querying live from externally hosted databases.
• Leverage and integrate Databricks Marketplace to consume high-quality third-party data and publish internal data assets securely.
• Experience with cloud-based services relevant to data engineering, data storage, data processing, data warehousing, real-time streaming, and serverless computing.

Govern and manage Delta Sharing for securely sharing datasets with external partners or across tenants.

Good to Have :