Azure Data / Search Engineer

VeeRteq Solutions Inc
Irving, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Irving, United States of America

Tech stack

API
Artificial Intelligence
Application Services
Azure
Big Data
Mobile Application Development
Cloud Computing
Cloud Computing Security
Cloud Engineering
Code Review
Databases
Information Engineering
ETL
Relational Databases
Linux
DevOps
Distributed Systems
Elasticsearch
JSON
Python
PostgreSQL
Machine Learning
Microsoft SQL Server
Search Technologies
Software Deployment
Software Engineering
SQL Databases
Data Streaming
Enterprise Search
Enterprise Data Management
Data Logging
Pulumi
Enterprise Software Applications
Data Ingestion
Azure
GitHub Copilot
Large Language Models
Backend
GIT
FastAPI
Event Driven Architecture
Data Lake
PySpark
Low Latency
Deployment Automation
Kafka
REST
Terraform
Data Pipelines
Bamboo
Docker
Confluent
Databricks
Microservices

Job description

Looking for a strong Azure Data Engineer / Senior Software Engineer with strong expertise in Python, Databricks, SQL, Elasticsearch, Kafka, and Azure, responsible for building scalable search platforms, REST APIs, event-driven data pipelines, and cloud-native distributed systems supporting high-volume enterprise applications.

Roles and Responsibilities: -

Resource will be responsible to design, build, and support client, our enterprise search and intelligent matching platform.

This role will develop scalable APIs, high-performance search capabilities, event-driven data pipelines, and cloud-native services supporting millions of transactions daily.

The consultant will work across Azure, Elasticsearch, Kafka, Databricks, Python, and distributed systems to build highly available, low-latency applications.

The ideal candidate has strong backend engineering experience with cloud-native architectures, search technologies, REST APIs, event streaming, and large-scale data processing.

Design and develop scalable backend services using Python. Build and maintain REST APIs supporting enterprise applications. Design and optimize Elasticsearch indexes, queries, mappings, and search relevance.

Develop intelligent search and matching capabilities for large-scale datasets. Build event-driven architectures using Kafka and Azure Event Hub. Design high-throughput data ingestion and indexing pipelines. Integrate applications with Databricks and enterprise data platforms.

Develop secure cloud-native applications on Microsoft Azure. Implement CI/CD pipelines and automated deployment processes.

Monitor application health, logging, observability, and production performance. Optimize API response time, indexing performance, and infrastructure utilization. Participate in architecture, design reviews, code reviews, and production support.

Collaborate with product managers, architects, data scientists, and engineering teams.

Requirements

Engineering Degree BE/ME/BTech/MTech/BSc/MSc.

Technical certification in multiple technologies is desirable.

Skills: -

Mandatory skills

Programming Python (required) SQL REST APIs JSON FastAPI (preferred) Async Python Cloud Microsoft Azure Azure App Services Azure Linux VMs Azure Container Apps / AKS (preferred) Azure Managed Identity Azure Key Vault Azure Storage Azure Monitor Azure Event Hub Search

Technologies Elasticsearch Query DSL Relevance tuning Mapping design Aggregations Multi-search (msearch) Bulk indexing Search optimization Index lifecycle management Event Streaming Apache Kafka Confluent Cloud Producers / Consumers Kafka Connect Schema Registry

Event-driven architecture Data Engineering Databricks PySpark Delta Lake Data ingestion pipelines ETL/ELT DevOps Git Azure DevOps Azure Pipelines CI/CD Docker Infrastructure as Code (Terraform or Pulumi preferred) Databases PostgreSQL SQL Server Relational Databases Required

ExperienceMin 8+ years of software engineering experience. Strong Python backend development experience. Experience designing and operating production REST APIs.

Strong experience with Elasticsearch in production environments. Experience building scalable search platforms. Experience with Kafka or enterprise event-streaming platforms. Experience deploying applications on Microsoft Azure. Experience with CI/CD pipelines and automated deployments.

Experience troubleshooting production systems and performance issues. Strong understanding of distributed systems and microservices.

Preferred Qualifications:

Experience with AI-assisted search or intelligent matching platforms. Experience with Databricks and Delta Lake.

Experience with machine learning integration. Experience with semantic search or vector search.

Experience with Azure OpenAI or LLM integration. Healthcare or supply chain experience. Experience using GitHub Copilot or Codex.

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