Data Architect - ETL/Snowflake DB

Key Responsibilities

Data Architecture & Strategy :

• Lead the design and architecture of highly scalable, robust, and efficient data solutions leveraging Snowflake as the primary data platform.
• Develop and implement enterprise-level data architecture strategies, blueprints, and roadmaps that align with business objectives and growth.
• Architect and manage data solutions, optimizing performance for complex analytical workloads and high-volume reporting requirements.
• Collaborate with cross-functional teams (e.g., analytics, engineering, business stakeholders) to deeply understand business needs and translate them into well-defined, robust data architectures and technical specifications.
  

Data Engineering & Implementation

• Design, implement, and optimize end-to-end data pipelines, data warehouses, and data lakes, ensuring efficient, reliable, and automated data ingestion, transformation (ELT/ETL), and loading processes into Snowflake.
• Develop and maintain advanced SQL queries, stored procedures, and data models within Snowflake for complex data manipulation and analysis.
• Ensure data quality, consistency, and integrity across all data solutions.
  

Data Governance & Security

• Develop and enforce best practices for data governance, data security, access control, auditing, and compliance within the cloud-based data environment (Snowflake).
• Implement data masking, encryption, and other security measures to protect sensitive data.
  

Technology Evaluation & Integration

• Evaluate, recommend, and integrate third-party tools, technologies, and services to enhance the Snowflake ecosystem, optimize data workflows, and support the overall data strategy.
• Stay abreast of new Snowflake features, industry trends, and data technologies, recommending their adoption where beneficial.
  

Mentorship & Collaboration

• Provide technical leadership and mentorship to data engineers and other team members, fostering a culture of best practices and continuous improvement.
• Facilitate effective communication and collaboration across global teams.
  

Required Skills & Qualifications

• Experience : 5-7+ years of progressive experience in data architecture and data engineering roles.
• Snowflake Expertise : Proven, in-depth hands-on experience as a data architect with extensive knowledge of Snowflake's architecture, features, and best practices (e.g., virtual warehouses, clustering keys, semi-structured data, time travel, Snowpipe, external stages, data sharing).
• SQL Mastery : Exceptional proficiency in advanced SQL for complex data manipulation, query optimization, and data modeling in a high-volume data environment.
• Data Warehousing/Lake Design : Strong experience in designing and implementing scalable data warehouses and data lakes.
• ETL/ELT : Hands-on experience with data ingestion, transformation, and loading processes (ETL/ELT).
• Cloud Data Platforms : Experience with other cloud data platforms (AWS, Azure, GCP) is a plus, but Snowflake expertise is paramount.
• Analytical Thinking : Strong analytical, problem-solving, and critical thinking skills with the ability to translate business requirements into technical solutions.
• Communication : Excellent verbal and written communication skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.
• Independent Work : Proven ability to work independently, manage multiple priorities, and deliver high-quality results in a remote setting.
• Time Zone Overlap : Must be able to overlap working hours until at least 10 :00 AM CST (US Central Time). This typically means starting late in India or working split shifts.
• Immediate Availability : Candidates who can start immediately or with a very short notice period are strongly preferred.
  

Education

• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related quantitative field. Master's degree is a plus.