TELECOMMUTE Data Architect

Hexaware Technologies

United States

22 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Artificial Intelligence Code Review Databases Continuous Integration Data Architecture Data Validation Data Discovery Data Infrastructure Digital Assets Java Database Connectivity JSON Python (Programming Language)

+20 more

Meta-Data Management Microsoft SQL Server Modular Design MongoDB OAuth Role-Based Access Control Power BI Standard Sql Microsoft SharePoint Data Streaming YAML Snowflake Git Data Lakes Pyspark Data Management Tools for Reporting Restful APIs Azure Synapse Analytics Databricks

Job description

Databricks: Medallion Architecture (Bronze/Silver/Gold), Delta Lake, Delta Live Tables (DLT), Auto Loader, Unity Catalog, Databricks Workflows, Databricks Apps, Databricks Genie
Languages: PySpark (expert), Python (PEP 8/PEP 20), SQL
Data Platforms: Azure Databricks, ADLS, Azure Synapse, Snowflake
Databases & Integration: MongoDB Atlas, SQL Server (JDBC), REST APIs, OAuth (SharePoint), cloudfiles
Governance: Unity Catalog - metastores, catalogs, schemas, RBAC, lineage, access policies
DevOps: Git, CI/CD for Databricks workflows and DLT pipelines, JSON/YAML config management
Reporting (nice-to-have): Power BI, DAX, Power Platform, * Designed and implemented end-to-end Lakehouse solutions on Azure Databricks across Bronze/Silver/Gold layers with schema enforcement and data quality checks
Delivered production-grade DLT pipelines and Auto Loader streaming ingestion from ADLS and external sources
Optimised PySpark jobs for performance and cost - partition tuning, caching, modular function-based code design

Unity Catalog & Governance

Implemented Unity Catalog as the foundational governance layer - metastores, catalogs, schemas, fine-grained RBAC, lineage, and audit controls
Standardised metadata management and data discovery across the platform

Data Architecture & Integration

Architected data flows from MongoDB Atlas, JDBC (SQL Server), REST APIs, and OAuth sources into the enterprise data platform
Established architectural standards for ingestion, transformation, and consumption layers; led architectural reviews across squads
Built configuration-driven (JSON/YAML) pipeline frameworks enabling scalable onboarding of new data sources

Databricks Genie

Familiar with Databricks Genie for enabling natural language querying of data assets and AI-assisted analytics for business users

Leadership

Mentored engineers on Databricks, PySpark, and Python best practices (PEP 8/PEP 20, naming conventions, modular design)
Conducted code reviews, enforced coding standards, and drove CI/CD adoption for Databricks workflows and DLT pipelines

Requirements

Required Experience : Data Platform, Integration, Azure Databricks & Lakehouse Specialist, Strong hands-on background in PySpark, Medallion Architecture, Delta Live Tables, Unity Catalog, and MongoDB Atlas integration. Familiar with Databricks Genie for AI-assisted analytics. An effective technical leader who sets architectural direction, mentors teams, and drives delivery. Exposure to Power BI and reporting solutions is a plus, not a core requirement.