Role: Principal Data Engineer
Duration: 12 months + extension (long term project)
Engagement: Contract/Freelance (full time, 5 days per week, 8 hour day)
Location: Onsite in Cork 3-4 days per week, remaining remote
General Summary: This position exists to architect and build enterprise-scale data infrastructure and platforms that enable the organization to collect, process, store, and deliver data efficiently and reliably. The Principal Data Engineer provides technical leadership in designing data solutions that support analytics, machine learning, and business intelligence initiatives across the organization. This role ensures data systems are scalable, performant, secure, and aligned with enterprise architecture standards and business objectives.
Duties & Responsibilities:
Design and implement enterprise data architecture, including data lakes, warehouses, and streaming platforms that support organizational data needs 25%
Build and optimize robust data pipelines and ETL/ELT processes to ingest, transform, and deliver data from diverse sources to downstream systems 20%
Provide technical leadership and mentorship to data engineering teams on best practices, design patterns, and emerging technologies 15%
Collaborate with stakeholders across data science, analytics, and business units to understand requirements and deliver scalable data solutions 15%
Establish and enforce data engineering standards, including data quality, governance, security, and performance optimization 10%
Evaluate and implement new data technologies, tools, and frameworks to enhance platform capabilities and team productivity 10%
Monitor and troubleshoot data infrastructure performance, ensuring high availability and reliability of data systems 5%
Knowledge, Skills and Abilities (KSAs):
Expert knowledge of data architecture patterns including data lakes, data warehouses, and lakehouse architectures
Advanced proficiency in programming languages such as Python, Scala, or Java for data engineering applications
Deep expertise with big data technologies and distributed processing frameworks such as Spark, Kafka, Airflow, or Flink
Strong experience designing and implementing cloud-based data platforms on AWS, Azure, or GCP
Knowledge of data modeling techniques for both relational and non-relational databases
Advanced SQL skills and experience with modern data warehouse platforms such as Snowflake, Redshift, BigQuery, or Databricks
Ability to architect solutions for data quality, data governance, and metadata management
Strong understanding of data security, compliance requirements, and privacy regulations
Proven leadership skills with ability to mentor engineers and influence technical direction
Excellent problem-solving abilities and capacity to make sound architectural decisions balancing technical and business considerations
Strong communication skills to articulate complex technical concepts to both technical and non-technical audiences
Work Experience &/or Education:
Bachelor's degree in Computer Science, Engineering, Information Systems, or related technical field
8+ years of experience in data engineering, with at least 3 years in a senior or lead technical role
Proven track record of designing and implementing large-scale data platforms and architectures
Demonstrated experience leading technical initiatives and mentoring engineering teams
Experience with cloud data platforms and modern data stack technologies