Snowflake Data Engineer

highly skilled Data Engineer

Key Responsibilities

• Design, develop, and maintain scalable

  ETL/ELT pipelines

  using

  Snowflake

  ,

  ADF

  , and

  Python

  to support

  data warehouse

  and

  datalake

  architectures.
• Build and automate

  data ingestion pipelines

  from various structured and semi-structured sources (APIs, flat files, cloud storage, databases) into Snowflake-based

  data lakes

  and

  data warehouses

  .
• Perform full-cycle

  data migration

  from on-premise and cloud databases (e.g., Oracle, SQL Server, Redshift, MySQL) to

  Snowflake

  .
• Optimize Snowflake workloads: schema design, clustering, partitioning, materialized views, and

  query performance tuning

  .
• Develop and orchestrate

  data workflows

  using

  Azure Data Factory

  pipelines, triggers, and dataflows.
• Implement

  data quality checks

  , validation processes, and monitoring mechanisms for production pipelines.
• Collaborate with cross-functional teams including Data Scientists, Analysts, and DevOps to support diverse data needs.
• Ensure

  data integrity, security, and governance

  throughout the data lifecycle.
• Maintain comprehensive documentation on pipeline design, schema changes, and architectural decisions.

Required Skills & Qualifications

• Bachelors degree in Computer Science, Information Technology, or a related field.

• 2+ years of hands-on experience with Snowflake

  , including Snowflake SQL,SnowSQL, Snowpipe, Streams, Tasks, and performance optimization.

• 1+ year of experience with Azure Data Factory (ADF)

  – pipeline design,linked services, datasets, triggers, and integration runtime.
• Strong

  Python

  skills for scripting, automation, and data manipulation.
• Advanced

  SQL

  skills – ability to write efficient, complex queries, procedures, and analytical expressions.
• Experience designing and implementing

  data lakes

  and

  data warehouses

  on cloud platforms.
• Familiarity with

  Azure cloud services

  , including Azure Data Lake Storage (ADLS), Blob Storage, Azure SQL, and Azure DevOps.
• Experience with

  orchestration tools

  such as Airflow, DBT, or Prefect is a plus.
• Understanding of

  data modeling

  ,

  data warehousing principles

  , and

  ETL/ELT best practices

  .
• Experience in building

  scalable data architectures

  for analytics and business intelligence use cases.

Preferred Qualifications (Nice to Have)

• Experience with CI/CD pipelines for data engineering (e.g., Azure DevOps, GitHub Actions).
• Familiarity with Delta Lake, Parquet, or other big data formats.
• Knowledge of data security and governance tools like Purview or Informatica.