Job highlights

- Expertise in Snowflake architecture,data warehousing,and cloud-native data platform design. . Proficiency in SQL and advanced database design principles for relational and semi-structured data. . Strong programming skills in Python with hands-on experience in PySpark and Apache Airflow for orchestrating data pipelines.
- Preferred Qualifications
- Work Experience

Job Title: Data Architect

Company: Feuji

Mode of Hire: Permanent Position

Experience: 15-18 Years

Work Location: Hyderabad

Work Timings : 5pm to 2 am IST

About Feuji

Feuji, established in 2014 and headquartered in Dallas, Texas, is a rapidly growing global technology services provider. With strategic locations including a Nearshore facility in San Jose, Costa Rica, and Offshore Delivery Centers in Hyderabad and Bangalore, we cater to a diverse clientele. Our team of talented engineers specializes in delivering cutting-edge solutions in managed cloud services, cybersecurity, product and quality engineering, and data-driven insights.

We collaborate with industry leaders such as Microsoft, HP, GSK, and DXC Technologies to empower organizations to achieve their business goals. At Feuji, we prioritize creating Happy Teams and fostering a culture of innovation, growth, and excellence.

Role Summary The Data Architect at Feuji is a senior-level role responsible for designing and implementing scalable, efficient, and AI-enabled data architectures primarily leveraging Snowflake cloud data platform. This position focuses on translating complex business requirements into robust data models and pipelines that support advanced analytics and AI-driven decision-making. The role ensures seamless integration of big data technologies and AI frameworks to optimize data flow, governance, and accessibility across the enterprise.

The Data

Architect will drive innovation in data warehousing and AI adoption, enabling Feuji s clients to harness data as a strategic asset.

Key Responsibilities





- Lead the design and deployment of Snowflake-based data warehouse architectures tailored to support AI and machine learning workloads.
- Architect and implement end-to-end data pipelines using Python, PySpark, Apache Airflow, and dbt to enable efficient ETL/ELT processes.
- Develop, optimize, and maintain complex data models and schemas to ensure high performance, scalability, and data integrity.
- Collaborate with data scientists and AI teams to integrate AI models and algorithms seamlessly into data workflows and pipelines.
- Oversee data ingestion from diverse sources, utilizing Hadoop ecosystems and Spark to handle large-scale and streaming data efficiently.
- Define and enforce data governance policies, quality standards, and security protocols within Snowflake environments.
- Monitor and tune Snowflake query performance, storage, and compute resource usage to maximize cost efficiency and throughput.
- Provide technical leadership and mentorship to data engineering teams on Snowflake best practices, AI integration, and big data technologies.

Skills

- Expertise in Snowflake architecture, data warehousing, and cloud-native data platform design.
- Proficiency in SQL and advanced database design principles for relational and semi-structured data.
- Solid programming skills in Python with hands-on experience in PySpark and Apache Airflow for orchestrating data pipelines.
- Deep understanding of big data tools including Spark and Hadoop ecosystems for batch and real-time data processing.
- Experience designing and implementing AI-ready data architectures that support machine learning model deployment.
- Familiarity with dbt for data transformation and version-controlled analytics engineering.
- Knowledge of data governance,



security best practices, and compliance standards in cloud environments.
- Ability to optimize data workflows for performance, scalability, and cost management within Snowflake.
- Strong analytical and problem-solving skills with a focus on innovative data solutions.
- Excellent communication and collaboration skills for working with cross-functional teams and stakeholders.

Education

- Minimum: Bachelor s degree in Computer Science, Information Technology, Data Science, or a related technical field.
- Preferred: Master s degree or higher in Data Engineering, Computer Science, or Business Analytics.
- Relevant certifications such as Snowflake SnowPro Advanced Architect, Certified Data Management Professional (CDMP), or equivalent.

Work Experience

- 15-18 years of progressive experience in data architecture, data engineering, or a related field.
- Demonstrated expertise designing and implementing large-scale Snowflake data warehouses and AI-integrated data solutions.
- Proven track record in leading complex data transformation projects involving Python, Spark, Hadoop, and cloud technologies.
- Experience working in enterprise environments with cross-functional teams to deploy high-impact data architectures.

Preferred Qualifications

- Certification in Snowflake architecture or advanced cloud data platform certifications.
- Hands-on experience with AI frameworks and machine learning model deployment in production data environments.
- Prior experience working in agile and DevOps-driven data engineering teams.
- Familiarity with additional cloud platforms such as AWS, Azure, or Google Cloud Platform in context of data services.
- Exposure to emerging data engineering tools and frameworks beyond core big data technologies.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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