Senior Data Engineer

Position Details

Title: Senior Data Engineer

Type: 3-6 months with potential to convert

Location: Hybrid in Oak Park Heights MN (3 days onsite per week)

Tech Stack: Snowflake dbt Fivetran Azure (ADO Blob Functions etc)

Role Overview

We are seeking a seasoned Senior level data Engineer to lead technical execution and provide architectural guidance across our onshore and offshore engineering this role you will be the primary technical point of contact ensuring that complex data requirements are translated into scalable resilient and highly optimized solutions. You will not only build but also influence the standards for a modern data stack centered on Snowflake and Azure driving Governance as Code and operational excellence.

Key Responsibilities

1. Technical Leadership & Cross-Shore Guidance

Engineering Anchor: Act as the primary technical lead for distributed teams ensuring clarity in requirements and maintaining high standards of execution across time zones.

Architectural Blueprinting: Engage with Product Owners and Solution Architects to design optimal data product pipelines that serve as the foundational reference for the broader engineering team.

Resilience Engineering: Design systems for high availability and fault tolerance ensuring the data platform can recover gracefully from upstream failures.

2. Data Platform & Pipeline Engineering

Modern Data Stack Mastery: Engineer and optimize full-lifecycle data pipelines using Fivetran Snowflake and dbt focusing on large-scale complex datasets.

Metadata-Driven Automation: Design and implement config-driven or metadata-driven pipelines to increase development velocity and reduce manual overhead.

Layered Frameworks: Apply advanced modeling techniques (Data Vault Dimensional/Star Schema) to create high-performance curated reusable core datasets and purpose-built datasets optimized for analytics and AI.

3. Performance & Cost Optimization

Snowflake Expert: Apply advanced proficiency in Snowflake performance tuning (clustering warehouse profiling query optimization) to minimize both latency and Azure consumption costs.

End-to-End Efficiency: Monitor and tune the entire flow from ingestion to transformation to ensure the stack remains performant as data volumes scale.

4. Governance Security & DataOps

Governance as Code: Implement and validate automated data lineage quality checks and data classification within the CI/CD workflow.

Observability & Health: Drive platform reliability by implementing end-to-end observability; proactively monitor data health and enforce rigorous quality gates using dbt.

Azure Int-egration: Manage and optimize data flows within the Azure ecosystem leveraging Azure DevOps (ADO) Blob Storage and Azure Functions.

Required Qualifications

Experience: 8 10 years of experience building and optimizing large-scale complex data architectures and pipelines.

Core Stack: Expert-level command of Snowflake dbt and Fivetran.

Cloud Infrastructure: Strong proficiency in Azure services (Storage Compute and DevOps/CI/CD).

Modeling: Proven ability to engineer layered data frameworks using various modeling methodologies (e.g. Data Vault 2.0).

Leadership: Experience guiding offshore teams and conducting technical code reviews to ensure consistency and adherence to patterns.

Preferred Good to Have Skills

AI/ML Enablement: Experience in building data foundations that enable Machine Learning and Generative AI use cases (e.g. Vector databases feature stores).

Advanced Governance: Experience with automated data privacy/masking and advanced metadata cataloging.

If this role aligns with your background and interests feel free to reply with your updated resume or availability to discuss further.