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, CDGC, 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.