Senior Snowflake & Azure Data Engineer

Job Description

We are seeking a highly specialized, strictly hands-on Senior Data

Engineer to design, develop, and maintain the complex data pipelines

that enable reliable data integration and delivery across the

enterprise.

Please Note: This is a purely technical, individual contributor role.

We are looking for hands-on data management and development of data

pipelines NOT architecture oversight, management, or production

support.

The Ideal Candidate (What We Are Truly Looking For)

To be successful in this role, you must be a practitioner who writes

code daily. Based on our technical bar, the ideal candidate possesses:

Deep Snowflake Expertise: You don't just use Snowflake; you understand

its architecture and leverage its absolute latest features. You must

have at least 6 years of recent, deeply hands-on experience

specifically within the Snowflake ecosystem.

Advanced SQL & Logic Skills: Your SQL logic is flawless. You have a

deep understanding of complex SQL concepts and can solve intricate

data problems without leaving gaps or writing incomplete queries.

Strong dbt Prowess: You have substantial, proven experience using dbt

(Data Build Tool) for modern data transformations.

High Accountability & Professionalism: You are fiercely accountable

for deadlines and deliverables. You work hard, manage your own time

effectively, and communicate proactively.

Key Responsibilities

Pipeline Development: Design, build, and deploy robust data pipelines

that extract, transform, and load (ETL/ELT) data from various sources

into our data storage systems using Informatica IDMC, Azure Data

Factory, and dbt.

Data Integration & Transformation: Integrate data from databases, data

warehouses, APIs, and external systems. Apply complex data cleansing,

aggregation, filtering, and enrichment techniques to make raw data

highly usable.

Performance Optimization: Monitor, tune, and optimize data pipelines

and processing workflows for scalability. Identify bottlenecks and

implement caching/indexing strategies to ensure lightning-fast query

performance.

Data Quality Assurance: Implement rigorous data quality checks and

validations within pipelines to ensure absolute accuracy, consistency,

and integrity.

Cross-Functional Collaboration: Partner effectively with architects,

data scientists, AI engineers, and analysts to optimize models and

govern enterprise information assets.

Required Technical Qualifications

Overall Experience: 8+ years of dedicated Data Engineering experience

(data modeling, ETL/ELT, data warehousing, master data management).

Snowflake: 6+ years of heavy, recent, hands-on experience in the

Snowflake ecosystem.

SQL & dbt: Mastery of complex SQL programming and deep, practical

experience with dbt.

Microsoft Azure Stack: Extensive hands-on experience with SQL Server

(IaaS, PaaS), Azure Synapse, Azure Data Factory (ADF), Azure

Databricks, CosmosDB, and Power BI.

Informatica: Extensive experience with Informatica IDMC (Cloud Data

Integration, CD MDM, Data Quality).

Programming: Proficiency in programming languages such as Python, C#, or Java.

Professional Expectations & Soft Skills

Deliverable-Obsessed: You take total ownership of your work streams.

You meet your deadlines and deliver high-quality code without needing

to be micromanaged.

Global Collaboration: Because this role interacts with teams in

Ireland, you must possess the schedule flexibility required for

cross-time zone coordination.

Clear Communicator: You can translate complex, technical information

into straightforward language for senior leadership and non-technical

stakeholders.

Critical Problem Solver: You think creatively, recognize trends in

complex data, and proactively look for solutions to technical

roadblocks.

Team Player: You treat everyone with respect, value diverse

perspectives, assume positive intent, and stay composed during

challenging, fast-paced deliverables.

Nice-to-Haves

Certifications in Snowflake, Azure Data Engineer, or dbt.

Previous experience in the professional services, accounting industry,

or working within a managed services provider (MSP) environment.

Previous client service or consultative experience.

Interview Process

30-minute technical deep-dive with the Hiring Manager (Expect rigorous

SQL, dbt, and Snowflake scenario questions).

30-minute interview with the Director.