Data Engineer (Senior Consultant) - Financial Services Technology Consulting 1726387
Location: Dublin (Hybrid: 2-3 days per week onsite)
Eligibility Requirements:
- Must be an EU or Irish Citizen, or hold a valid Stamp 4 Visa.
- Please note: Visa sponsorship is not available for this position.
Experience Level: 3+ Years (Mid-Level / Senior Consultant)
Core Stack: Advanced SQL, Azure (Data Factory/Synapse), Snowflake, or Databricks (Spark)
The Opportunity
We are seeking a talented, hands-on Data Engineer to join our Financial Services Technology Consulting practice. In this role, you will work directly with business and analytics teams at premier financial institutions to design, develop, and operate robust data pipelines. You will be responsible for transforming messy, raw corporate data into structured, production-ready formats for downstream analytics and reporting.
Key Responsibilities
- Build ETL/ELT Pipelines: Design, implement, and maintain scalable data ingestion and transformation pipelines using cloud-native tools.
- Database Optimization: Identify data pipeline bottlenecks, optimize complex query performance, and tune data storage platforms to handle high volumes.
- Ensure Compliance & Security: Build encryption, role-based access controls (RBAC), and data masking into pipelines to satisfy strict regulations (e.g., GDPR, financial risk standards).
- Agile Collaboration: Work closely with technical architects, product owners, and business leads in a fast-paced, Agile software delivery environment.
Key Requirements
- Experience: 3+ years of dedicated Data Engineering experience within a consulting firm, multinational corporate setting, or large financial institution.
- Advanced SQL: Expert-level SQL skills for complex data manipulation (advanced joins, subqueries, and window functions).
- Cloud Data Platforms: Hands-on experience in at least one of the major ecosystems:
- Microsoft Azure: Azure Data Factory (ADF), Synapse, Azure SQL, Data Lakes.
- Snowflake: Virtual warehouses, architecture, Streams & Tasks, Snowpark.
- Databricks: Apache Spark, Delta Lake, Structured Streaming.
- Programming & DevOps: Solid foundational knowledge of Python (standard libraries/data types) and familiarity with CI/CD deployment tools (GitHub, Azure DevOps, or Terraform).
