Big Data Architect / Data Architect (Hands-On Coding) at CHABEZ TECH LLC

Atlanta, Georgia, United States -

Full Time

Start Date

Immediate

Expiry Date

05 May, 26

Salary

0.0

Posted On

04 Feb, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Data Architecture, Python, SQL, Scala, Java, Distributed Systems, Data Modeling, Big Data, Spark, Hadoop, Kafka, Snowflake, Redshift, Cloud Platforms, AWS, Azure

Industry

IT Services and IT Consulting

Description

Company Description About Chabez Tech Chabez Tech is a Data Engineering & AI Products company headquartered in Pennsylvania, focused on digitally transforming businesses and helping them achieve operational and customer excellence. We deliver scalable data solutions, advanced AI frameworks, and long-term platform implementation support. This position supports a strategic internal platform initiative to enhance our own digital analytics and reporting capabilities. Job Description Big Data Architect / Data Architect (Hands-On Coding) Location: Atlanta, GA (Onsite) Engagement: Long-Term Contract (C2C) Experience Required: 15+ Years About Chabez Tech Chabez Tech is a Data Engineering and AI Products company delivering scalable, cloud-native solutions that help organizations achieve operational and customer excellence. Headquartered in Pennsylvania, we partner with enterprises to digitally transform their data ecosystems through modern data engineering, AI, and platform solutions. We specialize in building robust data platforms, accelerating product initiatives, and enabling operational efficiency through flexible, customizable solutions across industries. Role Overview We are seeking a highly experienced Big Data Architect / Data Architect with strong hands-on coding expertise to design, build, and scale modern data platforms. This role requires deep expertise in data architecture, distributed systems, and cloud-native big data technologies, along with the ability to contribute directly through development. Key Responsibilities Design and implement end-to-end big data architectures for large-scale, high-volume systems Lead data modeling efforts across dimensional, relational, and NoSQL models Develop and optimize distributed data processing pipelines Provide hands-on development using Python, SQL, and Spark-based frameworks Architect and implement cloud-native data solutions Collaborate with cross-functional teams to deliver scalable, secure, and high-performance data platforms Ensure best practices for performance, scalability, reliability, and data governance Required Skills & Experience 15+ years of experience in Data Engineering / Data Architecture Strong hands-on coding experience in: Python (preferred) Advanced SQL Scala or Java (nice to have) Strong understanding of distributed systems and large-scale data processing Expertise in data modeling (dimensional, relational, NoSQL) Proven experience designing enterprise-grade data architectures Big Data & Data Technologies Big Data Frameworks: Spark, Hadoop, Kafka Databases / Data Warehouses: Snowflake, Redshift, BigQuery, Azure Synapse Data Lakes: Amazon S3, Azure Data Lake Storage (ADLS), Google Cloud Storage (GCS) ETL / ELT Tools: Airflow, dbt, Informatica, Talend (any one or more) Cloud Platforms Experience with at least one major cloud provider: AWS or Azure or GCP Strong experience designing and implementing cloud-native data architectures Nice to Have Experience working in large enterprise environments Strong communication and technical leadership skills Ability to mentor engineers and influence architectural decisions Thanks & Regards Utsav Burman Head North America Ops ChabezTech LLC 4 Lemoyne Dr #102, Lemoyne, PA 17043, USA Phone: +1-717-441-5440 (US) | +91-8097 164 089 ( India ) Email: utsav@ chabeztech.com | www.chabeztech.com GSA Multiple Award Schedule (MAS) | E-Verify Company Additional Information All your information will be kept confidential according to EEO guidelines.

Responsibilities

The Big Data Architect will design and implement end-to-end big data architectures for large-scale systems and lead data modeling efforts. They will also develop and optimize distributed data processing pipelines and collaborate with cross-functional teams.