Data Engineer (Snowflake)

Data Engineer

6 months contract to  start, extension/conversion

Dublin CA – 2 days a week onsite hybrid

 Local candidate who can be onsite at least 2 day/week ideal

• 7 yrs IT exp, 5+ atleast in data platforms (7-10 YOE is ideal, nothing over 15 YOE)
• Snowflake: MUST
• Azure: MUST
• Python: MUST
• SQL: MUST, including complex/advanced SQL

JD:

The role is focused on platform engineering, including platform management, monitoring, performance optimization, production support, automation, and cost management, while also evaluating and enabling emerging technologies and architectural patterns such as lakehouse architectures, open table formats (e.g., Apache Iceberg), modern data platform services, and next-generation analytics capabilities. Success in this position requires strong hands-on technical expertise, including the ability to develop and troubleshoot solutions using SQL and Python, a proactive approach to problem-solving, a strong sense of ownership and accountability, and the ability to independently diagnose and resolve complex technical issues while driving continuous improvement across the platform.

QUALIFICATIONS & SPECIAL SKILLS REQUIRED

•    Minimum 7 years of IT experience in data technologies, including experience supporting, engineering, and operating enterprise data and analytics platforms in cloud-based environments.
•    5+ years of hands-on experience with Snowflake and modern cloud-based data platforms, including technologies such as dbt, Azure, and related data ecosystem tools. Experience with Snowflake administration, performance tuning, security, operational support, and cost optimization is highly desirable
•    Strong experience with SQL and Python for automation, diagnostics, troubleshooting, operational support, and platform improvements. Experience designing, implementing, and supporting CI/CD pipelines, source control practices, deployment automation, and DevOps processes for data platform solutions
•    Solid understanding of data warehousing, ELT/ETL frameworks, orchestration, data modeling, APIs, analytics/reporting platforms, and modern cloud data architectures
•    Experience monitoring, troubleshooting, and optimizing production platforms, including observability, incident management, root-cause analysis, performance tuning, and reliability improvements
•    Knowledge of cloud cost management, platform governance, and emerging data technologies such as lakehouse architectures, open table formats (e.g., Apache Iceberg), and next-generation analytics platforms.
•    Strong analytical, problem-solving, and communication skills, with a demonstrated ability to take ownership, work independently, quickly learn new technologies, and collaborate effectively across technical and business teams