Forward Deployed Engineer - Cloud Data Engineering

Hexaware Technologies; Mumbai, Pune District, Chennai District; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

Hexaware Technologies is seeking a senior Databricks Architect/Data Engineer to design and implement a Databricks Lakehouse architecture for client environments. You will govern Unity Catalog, manage security policies, and enable Delta Sharing across clouds.

The role requires building AI-ready pipelines with vector search and robust monitoring for data quality and job health. Qualified candidates will have 9–12 years in IT, with 5+ years hands-on Databricks production experience, and strong

Qualifications

• 9-12 years of overall IT experience with 5+ years in production Databricks.
• Hands-on experience in cloud-based data engineering and lakehouse architectures.
• Strong design, implementation and support experience for data lakehouse architectures.

Responsibilities

• Design and build a Databricks Lakehouse architecture tailored to client context.
• Implement Unity Catalog governance with multi-level namespaces and security features.
• Develop AI-ready data pipelines including embedding generation and semantic search indexing.
• Set up end-to-end monitoring for data quality and job failures.

Skills

Databricks Lakehouse Platform

Delta Lake

Unity Catalog

Delta Live Tables

Databricks Workflows

Databricks SQL

Multi-Cloud Data Engineering

Azure

AWS

GCP

Python

PySpark

Pandas

Boto3

Delta API

SQL

Tools

Databricks

OpenLineage

Docker

Kubernetes

GitHub Actions

Azure DevOps

Snowflake

Job description

• 9-12 years of overall experience in IT, Data Engineering, and a minimum of 5 years of hands-on experience with Databricks in production environments, in cloud-based data engineering, with a strong background in designing, implementing, and supporting modern data lakehouse architectures.


• Design and build Databricks Lakehouse architecture specific to the client''s context: Unity Catalog hierarchy, cluster policies, network configuration (VNET injection or Private Link), and medallion layer design justified against their security, compliance, and budget constraints


• Implement Databricks Unity Catalog governance: three-level namespace design (metastore/catalogue/schema), column-level lineage, dynamic data masking, row-level security, and Delta Sharing for cross-cloud data access


• Build AI-ready data pipelines: embedding generation workflows, document chunking and indexing pipelines, and semantic search indices using Databricks Vector Search


• Implement end-to-end monitoring: Databricks job failure alerts, data freshness SLA checks, row count anomaly detection, data quality expectation failures via DLT

Primary Skills

• Databricks Lakehouse Platform


• Delta Lake


• Unity Catalog


• Delta Live Tables


• Databricks Workflows


• Databricks SQL


• Multi-Cloud Data Engineering


• Azure (Synapse, ADF, ADLS Gen2) or AWS (S3, Glue, Redshift) or GCP (BigQuery, Dataflow)


• Python


• PySpark


• Pandas


• Boto3


• Delta API


• SQL

Secondary Skills

• Apache Kafka / Azure Event Hubs / AWS Kinesis


• Databricks Structured Streaming


• Databricks MLflow


• Databricks AI Assistant


• Snowflake


• OpenLineage / Databricks Unity Catalog lineage


• Azure DevOps / GitHub Actions


• Cloud Cost Management / Databricks DBU optimisation


• Docker / Kubernetes


• REST / GraphQL API Integration


• Data Governance Frameworks


• GitHub Copilot

Location

Chennai,Mumbai,Pune,Bengaluru,Hyderabad,Noida,Ahmedabad.