Solution Architect

Key Responsibilities

Architecture Design: Develop end-to-end data architecture leveraging Snowflake, or Databricks for data engineering and data warehousing.

Integration: Design and implement seamless integration between Databricks, Snowflake, and other cloud services (AWS/Azure/GCP).

Data Strategy: Define best practices for data ingestion, transformation, storage, and governance.

Performance Optimization: Ensure high performance and cost efficiency across data pipelines and queries.

Security & Compliance: Implement robust security, access control, and compliance frameworks.

Stakeholder Collaboration: Work with business teams to translate requirements into technical solutions.

Innovation: Stay updated on emerging technologies and recommend improvements to the data ecosystem.

Technical Expertise:

Strong experience with Databricks (Spark, Delta Lake, MLflow).

Proficiency in Snowflake (data modeling, query optimization, Snowpipe).

Hands-on experience with Python, SQL, and ETL frameworks.

Cloud Platforms: AWS, Azure, or GCP experience.

Data Architecture: Knowledge of modern data lakehouse and warehouse patterns.

Security & Governance: Familiarity with data governance tools and practices.

Soft Skills: Excellent communication, problem-solving, and stakeholder management.

Strong experience with Databricks (Spark, Delta Lake, MLflow).

Proficiency in Snowflake (data modeling, query optimization, Snowpipe).

Hands-on experience with Python, SQL, and ETL frameworks.

Certifications: Databricks Certified Data Engineer, Snowflake SnowPro Core, and relevant cloud certifications.

Experience with orchestration tools (Airflow, dbt).

Exposure to AI/ML workflows and streaming data.

Required Skills & Qualifications Preferred Qualifications