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Location: Sunnyvale, California (CA)
Contract Type: C2C
Posted: 3 weeks ago
Closed Date: 05/20/2026
Skills: Snowflake Data Engineering , PyTorch| TensorFlow
Visa Type: Any Visa

Role: Sr. Snowflake Data Engineer AI/ML

Location: Location: Sunnyvale, CA-Need Locals

Duration:6 + Months

 

Note: Must need LinkedIn Profile in Submission and candidate must be local to Bay Area. As Customer is not considering relocation candidates for this role.

 

MUST HAVE:

  • Hands-on experience with writing Complex queries using – Joins, Self Joins, Views, Materialized Views, Cursor also Recursive, use of GROUP BY, PARTITION BY functions / SQL Performance tuning
  • Hands-on experience with ETL and Dimensional Data Modelling – Slowly Changing Dimensions (SCD – Type 1, 2, 3)

Good understanding of concepts like schema types, table types - fact-dimension etc. like how to design a dimension vs fact, design considerations factored etc.

  • Proficiency in Python scripting/programming – using Pandas, PyParsing, Airflow.

Pandas, Tableau server modules, Numpy, Datetime, Apache Airflow related modules, APIs

Setting up Python scripts on DataLab, scheduling processes, connecting with DataLake (S3 etc )

Data Pipeline automation

Strong Python programming skills

Apache Kafka and Python (using client libraries like Confluent's librdkafka or kafka-python; to send (produce) and receive (consume) messages from Kafka topics.

Experience building streaming applications, data pipelines, and microservices etc.)

  • Good understanding on Snowflake Architecture - experience with designing and building solutions.

 

Architecture, design aspects, performance tuning, time travel, warehouse concepts - scaling, clustering, micro-partitioning

Experience with SnowSQL, Snowpipe

 

  • Good to Have - Experience with Snowflake performance optimization techniques
  • Experience with Vertica, Singlestore
  • Lead Experience - Experience interacting with business and independently develop and lead data projects. Collaborating with Offshore and owning overall project delivery.
  • Actively participating in discussions with business to understand requirements, perform thorough impact analysis and provide suitable solutions.

 

Role Descriptions: Key Qualifications

  • MUST have Snowflake Data Engineering 
  • Design and implement enterprise grade data pipelines using Snowflake| including ingestion and transformation
  • Must be strong in both Core and Semantic aspects
  • Develop complex SQL transformations| stored procedures and Dynamic tables inside Snowflake to enable near real time and batch processing
  • Implement Snowflake data sharing| data marketplace integrations
  • Engineer Snowpipe and Kafka to Snowflake streaming ingestion pipelines also handling high throughput event data at scale
  • Optimize Snowflake cluster performance virtual warehouse sizing| query profiling| clustering keys
  • Architecture| design aspects| performance tuning| time travel| warehouse concepts  scaling| clustering| micro partitioning
  • Experience with Snow SQL| SnowpipeData Integration aspects
  • Design and maintain end to end ELT pipelines using Apache Airflow
  • Experience in building reusable parameterized data ingestion pipelines frameworks is beneficial.
  • Thorough data quality checks AI and Data Science
  • Integrate AI and LLMs with data pipelines via Python UDFs or API callouts enabling text analytics| semantic search and GEN AI augmented workflows
  • Experience with Python based frameworks like scikit learn| PyTorch| TensorFlow
  • Experience with NLP and text mining techniques on unstructured data to identify actionable information
  • Time series forecasting| anomaly detection and propensity modeling
  • Experience with Data Visualization aspect Hands on experience with writing Complex queries using Joins| Self Joins| Views| Materialized Views| Cursor also Recursive| use of GROUP BY| PARTITION BY functions   SQL Performance tuning Hands-on experience with ETL and Dimensional Data Modelling Slowly Changing Dimensions i.e. 1| 2| 3.
  • Good understanding of concepts like schema types| table types  fact dimension etc. like how to design a dimension vs fact| design considerations factored etc.
  • Proficiency in Python scripting programming using Pandas| PyParsing| Airflow. Pandas| Tableau server modules| NumPy| Datetime| Apache Airflow related modules| APIs
  • Data Pipeline automation Strong Python programming skills Actively participating in discussions with business to understand requirements| perform thorough impact analysis and provide suitable solutions.