Chief Data Infrastructure Architect

2 days ago

Guntur, Andhra Pradesh, India beBeeData Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Job Title: Senior Data Engineer

Overview

We are seeking an experienced Senior Data Engineer to lead the design and implementation of scalable, high-performance data pipelines using Snowflake and dbt. This includes defining architectural best practices and driving data transformation at scale.

Key Responsibilities:

  • Architect and implement modular, test-driven ELT pipelines using dbt on Snowflake.
  • Design layered data models (e.g., staging, intermediate, mart layers / medallion architecture) aligned with dbt best practices.
  • Lead ingestion of structured and semi-structured data from APIs, flat files, cloud storage (Azure Data Lake, AWS S3), and databases into Snowflake.
  • Optimize Snowflake for performance and cost: warehouse sizing, clustering, materializations, query profiling, and credit monitoring.
  • Apply advanced dbt capabilities including macros, packages, custom tests, sources, exposures, and documentation using dbt docs.
  • Orchestrate workflows using dbt Cloud, Airflow, or Azure Data Factory, integrated with CI/CD pipelines.
  • Define and enforce data governance and compliance practices using Snowflake RBAC, secure data sharing, and encryption strategies.
  • Collaborate with analysts, data scientists, architects, and business stakeholders to deliver validated, business-ready data assets.
  • Mentor junior engineers, lead architectural/code reviews, and help establish reusable frameworks and standards.
  • Engage with clients to gather requirements, present solutions, and manage end-to-end project delivery in a consulting setup.

Required Skills & Qualifications:

  • Bachelor's or master's degree in computer science, data engineering, or a related field.
  • Certifications such as Snowflake SnowPro Advanced, dbt Certified Developer are a plus.
  • 5 to 8 years of experience in data engineering roles, with 3+ years of hands-on experience working with Snowflake and dbt in production environments.

Technical Skills:

  1. Expert-level knowledge of SQL and Snowflake, including performance optimization, storage layers, query profiling, clustering, and cost management.
  2. Experience in dbt development: modular model design, macros, tests, documentation, and version control using Git.

Soft Skills & Leadership:

  • Ability to thrive in client-facing roles with competing/changing priorities and fast-paced delivery cycles.
  • Stakeholder Communication: Collaborate with business stakeholders to understand objectives and convert them into actionable data engineering designs.
  • Project Ownership: End-to-end delivery including design, implementation, and monitoring.
  • Mentorship: Guide junior engineers and establish best practices; build new skills in the team.
  • Agile Practices: Work in sprints, participate in scrum ceremonies, story estimation.

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