F2F -Hiring Alert !! EPAM !! GCP Data Engineer - Hyderabad!!

Dear Candidate,

Greetings from EPAM Systems -INDIA !!

We are planning for a face to face DRIVE at EPAM Hyderabad Premises. We are seeking an Experienced GCP DATA Engnieer.

Do apply - Reach Heights with EPAM !!

Role Need:

Location : All India EPAM

Interview Mode -Hyderabad Face to Face -17oct-26 - Saturday .

Years of Experience -5+years.

Required Tech Skills:

GCP BigQuery (advanced), Apache Iceberg, Delta Lake, Delta Sharing, Kafka/CDC, Python, Spark, data lake architecture, Iceberg UniForm, Snowflake Horizon catalog, Databricks Unity Catalog

AI Tooling Profficiency

Operative actively uses AI-assisted development tools across its engineering workflow. All resources are expected to have active, working experience with AI coding and productivity tools. Claude Code (Anthropic) is the preferred tool; demonstrated proficiency with GitHub Copilot, Cursor, or comparable tools is acceptable. Candidates should be prepared to demonstrate AI tooling use in a technical screening.

Responsibilities

Data Lake Architecture

Design and implement lakehouse UniForm write layer one physical dataset, dual-format metadata (Delta + Iceberg), readable by all target consumers without conversion

Establish and validate GCS-to-BigQuery ingestion pipeline patterns for structured operational data types (sales, delivery, schedule, performance)

Implement change-data-capture (CDC) patterns using Kafka for real-time and near-real-time data movement into the lakehouse

Develop dependency-aware bookkeeping and data lineage tracking patterns for use across all data pipelines

Ensure all adapter code is modular, version-controlled, and designed for reuse across new data source integrations

Snowflake Integration

Configure Iceberg external table definitions for Operative data products within Snowflake's Horizon catalog

Validate zero-copy read access from Snowflake to Operative-managed Iceberg / Delta tables without data movement

Implement and test tenant-scoped access controls compatible with Snowflake Horizon catalog metadata governance

Document integration pattern for re-use across additional data products

Databricks Integration

Implement and certify Delta Sharing adapter for live, zero-copy data sharing from Operative's Delta Lake tables to Databricks consumers

Configure Delta Sharing endpoint registration and sharing agreement management

Validate read access from Databricks via Delta Sharing protocol — Pandas, Spark, and other Delta-compatible consumers

Test end-to-end data freshness and sharing latency within agreed SLA targets

Governed Access Layer (Integration Exchange)

Operative operates a governed data access layer that controls all external data-out connectivity. This workstream requires the SI to implement connector registry entries, RBAC configurations, and tenant-scoped authorization for both the 

Snowflake and Databricks adapters. Specifically:

Register Snowflake and Databricks as named connector types in the connector registry

Implement RBAC and tenant-scoped authorization on all data-out paths — auditable and controlled per tenant

Implement metering hooks compatible with the billing framework for governed data-out flows

Validate authori

Warm Regards

Kalaichandran

[email removed]