Role: Senior Data Engineer (level 3)

Experience: 4-7 years’

Company: Kodiak

Job Summary

We are seeking a Senior Data Engineer to design, build, and optimize our modern data platform on Azure, with a solid focus on Snowflake modeling and DBT‑driven ELT. You will own end‑to‑end data pipelines in Azure Data Factory, implement scalable large‑file ingestion patterns, and deliver analytics‑ready datasets grounded in OLAP/warehouse best practices. The role includes establishing data quality, lineage, and governance standards; tuning performance and cloud costs across Snowflake and Azure services (Storage, Functions, Service Bus, Key Vault, Monitoring); and applying SQL Server expertise for integration and performance‑optimized querying.

You will apply strong engineering practices— tests, CI/CD, observability, and documentation—while providing technical leadership and mentorship to elevate team practices. Partnering closely with engineering, architects, and product managers, you’ll deliver trusted, well‑modeled data products and semantic layers that power downstream insights and applications at scale.

Key Responsibilities

● Apply OLAP and data‑warehouse best practices to design efficient, scalable data models and storage architectures.

● Design, develop, and maintain Snowflake data models supporting robust ELT workflows.



● Build and maintain DBT models to deliver reliable, well‑structured transformations and modular, testable data logic.

● Build, schedule, and orchestrate end‑to‑end data pipelines in Azure Data Factory to ensure reliable ingestion, transformation, and delivery of data.

● Handle large‑file ingestion and processing using scalable, high‑performance patterns.

● Manage complete ELT workflows integrating large‑file loading, DBT transformations, and Snowflake modeling into an optimized lifecycle.

● Utilize SQL Server for data extraction, integration, and performance‑tuned querying across enterprise datasets.

● Leverage core Azure services including Storage, Functions, Service Bus, Key Vault, and Monitoring to support secure, resilient, and maintainable data workflows.

● Optimize pipeline performance and manage cloud cost efficiency across Azure Data Factory, Snowflake, and supporting Azure components.

● Implement strong data‑quality processes, validation rules, and lineage tracking across Snowflake and Azure pipelines.

● Maintain comprehensive governance, security controls, and documentation across all data assets and workflows.

● Partner with engineering, analytics, and product teams to deliver clean, reliable, well‑modeled datasets that enable downstream insights and applications.

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