Mandatory Skills : ETL Concepts, Python for DATA, Snowflake
We are looking for a Senior Data Platform Engineer Candidate will design and operate data pipelines that connect heterogeneous source systems normalize data into consumptionready models in Snowflake and build AIpowered agents that surface intelligence across the platform
Core Responsibilities
Snowflake engineering Design schemas write performant SQL manage roles warehouse sizing and implement change management practices
ETL ELT development Build and maintain pipelines that ingest from diverse sources APIs databases event streams and normalize data for BI and downstream consumers
AI agent development Leverage Snowflake Cortex and AI agent frameworks to build intelligent data products and automate analytical workflows
Backend API connectivity Develop backend integrations with internal and thirdparty systems via REST APIs and backend services
Required Skills
Snowflake Handson experience building and optimizing data models writing advanced SQL PIVOT GROUPING SETS ROLLUPCUBE and managing Snowflake environments in production
Multisource integration Proven ability to connect and ingest data from heterogeneous sources including relational databases REST APIs SaaS platforms and event streams
ETL ELT design Experience designing normalized schemas and transformation pipelines that produce clean consumptionready data models starsnowflake schema dimensional modeling
Python Strong proficiency in Python for data engineering tasks pipeline orchestration data transformation API clients and scripting automation
AI agents within Snowflake Familiarity with Snowflake Cortex LLM functions and agentbased patterns for building intelligent datadriven workflows inside the Snowflake ecosystem
Backend integration patterns Practical experience building backend services and integrations using Python REST APIs and related tooling authentication pagination error handling retry logic
Additional skills
PostgreSQL relational databases Working knowledge of PostgreSQL or equivalent RDBMS including query optimization indexing and schema design patterns
Go Golang Experience building backend services or microservices in Go is a strong differentiator
Cloud data infrastructure Familiarity with Azure or AWS data services eg Azure Data Factory Event Hubs S3 as source or orchestration layers
Data observability testing Experience with data quality frameworks dbt tests or observability tooling Great Expectations Monte Carlo etc
Youre a selfdirected engineer who thrives at the intersection of data engineering and platform thinking You can navigate ambiguous requirements design for scale and communicate clearly across engineering and product stakeholders You care about data quality documentation and building systems that other teams love to consume
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