Senior Data Engineer

2 days ago

Gurgaon, Haryana, India Crossing Hurdles Full time

At Crossing Hurdles, we work as a referral partner. We refer candidates to our partner that collaborates with the worlds leading AI research labs to build and train cutting-edge AI models.

Position: Senior Data Engineer

Type: Hourly Contract

Compensation: $35-$70 per hour

Location: India (Remote)

Commitment: Flexible hrs/week)

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).

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