Analytics Engineer (Remote)

Crossing Hurdles

Position:

Type:

Compensation:

Location:

Commitment:

Role & Responsibilities

• Design, build, and maintain DBT models, macros, and tests following modular and semantic data modeling best practices.
• Integrate DBT workflows with Snowflake Cortex CLI for feature engineering, model training, inference, orchestration, and evaluation.
• Build and scale Snowflake-native data and ML pipelines leveraging Cortex AI/ML capabilities.
• Collaborate closely with data engineers, analytics engineers, and ML teams to operationalize AI-driven workflows.
• Establish best practices for DBTCortex architecture, governance, and usage patterns.
• Optimize Snowflake queries and compute for performance and cost efficiency.
• Build and maintain CI/CD pipelines for DBT using tools like GitHub Actions, GitLab, or Azure DevOps.
• Troubleshoot issues across DBT artifacts, Snowflake objects, data lineage, and data quality checks.
• Maintain clear documentation for data models, pipelines, testing frameworks, and architectural decisions.

Requirements:

• 3+ years of experience with DBT Core or DBT Cloud, including macros, packages, testing, and deployments.
• Strong hands-on expertise with Snowflake (warehouses, tasks, streams, materialized views, performance tuning).
• Hands-on experience with Snowflake Cortex CLI or strong ability to learn and adopt it quickly.
• Strong SQL skills with working familiarity in Python for scripting and DBT automation.
• Experience integrating DBT with orchestration tools such as Airflow, Dagster, or Prefect.
• Solid understanding of modern data engineering principles, ELT patterns, and version-controlled analytics workflows.
• Strong problem-solving skills with clear communication ability. Fluency in English.

Preferred:

• Experience operationalizing ML workflows within Snowflake.
• Familiarity with Snowpark and Python UDFs/UDTFs.
• Experience building semantic layers using DBT metrics.
• Exposure to MLOps or DataOps best practices.
• Experience with LLM workflows, vector search, or unstructured data pipelines.

Application Process:

• Apply for the job role.
• Await the official message/email from our recruitment team (typically within 1-2 days).