Senior Data Architect

Job Title: Senior Data Architect - Data Strategy and Engineering

Location: Global (Remote)

Job Type: Full-time

Job Description:

• We are seeking a highly skilled and experienced Senior Data Architect to join our team at Logic Pursuits. In this role, you will lead the design and implementation of scalable, high-performance data architectures using cutting-edge technologies.

• You'll work closely with clients to translate business needs into robust data solutions and play a key role in mentoring junior engineers, enforcing standards, and delivering production-grade data platforms.

• 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.

• 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.

Requirements:

• 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:

• Cloud Data Warehouse & Transformation Stack:

• Expert-level knowledge of SQL and Snowflake, including performance optimization, storage layers, query profiling, clustering, and cost management.

• Experience in dbt development: modular model design, macros, tests, documentation, and version control using Git.

• Orchestration and Integration:

• Proficiency in orchestrating workflows using dbt Cloud, Airflow, or Azure Data Factory.

• Comfortable working with data ingestion from cloud storage (e.g., Azure Data Lake, AWS S3) and APIs.

• Data Modelling and Architecture:

• Dimensional modelling (Star/Snowflake schemas), Slowly changing dimensions.

• Knowledge of modern data warehousing principles.

• Experience implementing Medallion Architecture (Bronze/Silver/Gold layers).

• Experience working with Parquet, JSON, CSV, or other data formats.

• Programming Languages:

• Python: For data transformation, notebook development, automation.

• SQL: Strong grasp of SQL for querying and performance tuning.

• Jinja (nice to have): Exposure to Jinja for advanced dbt development.

• Data Engineering & Analytical Skills:

• ETL/ELT pipeline design and optimization.

• Exposure to AI/ML data pipelines, feature stores, or MLflow for model tracking (good to have).

• Exposure to data quality and validation frameworks.

• Security & Governance:

• Experience implementing data quality checks using dbt tests.

• Data encryption, secure key management and security best practices for Snowflake and dbt.

• 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.

Benefits:

• Competitive compensation, flexible work options, and continuous learning culture.

About Us: