Live opening · Posted 10 hours ago
At a glance
The key details from the original listing.
About the role
Description supplied by the original job listing.
About the Role:
We are seeking a highly skilled and motivated Data Ingestion Engineer to join our data platform team. This role involves building and maintaining scalable, reliable, and secure data pipelines that power analytics, reporting, and decision-making across the organization.
You will work with Snowflake, SQL, dbt, Azure Data Factory (ADF), Python, and PostgreSQL o integrate and transform data from a variety of cloud and on-premises sources.
Key Responsibilities:
Design, develop, and maintain Snowflake-native data ingestion pipelines using Snowpipe, Snowpipe Streaming, Snow Tasks, and Snow Streams.
Build automated, scalable ingestion processes to load batch and near-real-time data into Snowflake.
Design and implement ELT workflows using Snowflake and dbt.
Integrate Azure Data Factory (ADF) with Snowflake for data movement and orchestration where appropriate.
Develop Python scripts and utilities for data ingestion, validation, automation, and integration.
Ingest data from APIs, databases, files, cloud storage, and other internal and external systems into Snowflake.
Monitor and optimize performance of pipelines and troubleshoot ingestion issues
Implement data quality checks, logging, alerting, and governance processes
Maintain technical documentation of data pipelines and workflows.
Required Skills & Experience:
4+ years of experience in data engineering, ETL development, or data integration
Strong hands-on experience with Snowflake data warehousing and data ingestion.
Hands-on experience with Snowpipe and/or Snowpipe Streaming.
Experience with Azure Data Factory (ADF) for orchestration and pipeline automation
Proficiency with Python for scripting, automation, and data manipulation
Experience building ETL/ELT pipelines and working with large data volumes.
Experience with dbt, preferably with Snowflake.
Solid working knowledge of Snowflake and PostgreSQL
Experience using dbt for SQL-based transformation, version control, and documentation
Strong SQL skills and familiarity with data modeling concepts (e.g., star/snowflake schemas)
Familiarity with Git and version-controlled development environments
Preferred Qualifications:
Experience with API integration and handling large data files (CSV, JSON, XML)
Familiarity with Azure Blob Storage, Azure Data Lake, or similar
Exposure to cloud data platforms (Azure, AWS, or GCP)
Understanding of data governance, lineage, and cataloging tools
Employment type
Full-time
Work arrangement
No
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