About this role
Overview
EC Markets is building a next-generation data platform to power trading, operational, and marketing intelligence. We are seeking a Senior Data Engineer to drive evolution of our Snowflake-based Data Lakehouse, establishing a modern data ecosystem that supports advanced analytics, compliance, and decision-making across the business.
This is a high-impact role for an experienced engineer with a track record of architecting and implementing scalable data platforms — ideally in financial or trading environments — who can talk and think data from ingestion to MI dashboards.
Key Responsibilities
Architecture & Development
- Assume ownership of a Snowflake-centric Data Lakehouse integrating structured, semi-structured, and unstructured data.
- Develop and support robust ETL/ELT pipelines that ingest and transform data from multiple internal systems (trading, CRM, finance, risk, etc.) and external APIs.
- Implement data models, schemas, and transformation frameworks optimised for analytical and regulatory use cases.
- Apply best practices in data versioning, orchestration, and automation using modern data engineering tools.
- Ensure scalability, data lineage, and governance across the data lifecycle.
Reports and data visualisation
- Build and own semantic models on top of Snowflake (DirectQuery and Import), using DAX, calculation groups, RLS/OLS, and incremental refresh.
- Develop operational reports, dashboards and data extracts
Data Governance & Quality
- Maintain high data integrity, privacy, and security aligned with FCA and GDPR requirements.
- Monitor and optimise query performance and storage efficiency.
Cross-Functional Collaboration
- Partner with business units (Trading, Finance, Marketing, Compliance, Operations) to capture data requirements and translate them into robust technical solutions.
- Support regulatory, management, and operational reporting requirements through structured data models.
Skills & Experience (Non-negotiable)
- Experience in financial services, trading, or fintech environments.
- Proven experience designing and delivering DWH / Delta Lakehouse using Snowflake.
- Expert level SQL and data modelling expertise (star/snowflake schemas, dimension/al modelling).
- 2+ years writing dbt models in production. Comfortable with sources, snapshots, tests, macros, exposures, and the medallion (bronze/silver/gold) pattern.
- 3+ years building production Power BI on enterprise warehouses. Expert DAX (time intelligence, variables, virtual relationships, calculation groups), Power Query / M, Tabular Editor, DAX Studio.
- Strong SQL on Snowflake. Understand warehouse sizing, clustering, query profiles, and the cost levers that matter.
- Familiarity with orchestration and transformation frameworks.
- Hands-on experience with data analysis, visualisation, and operational reporting tools.
- Excellent communication skills and ability to translate business requirements into scalable data architecture.
Skills & Experience (nice to have)
- Ability to create scripts in Python or another scripting language.
- Experience with AWS (ECS, S3, IAM), Terraform, Git/GitHub Actions.
- Power BI embedded, Fabric, or a credible opinion on when not to use them.
- Exposure to Microsoft Fabric Direct Lake, Snowflake Cortex / Claude.ai connector, or other AI-on-warehouse patterns.
Qualifications
- Degree in Computer Science, Data Engineering, or related field.
- 5–8 years of hands-on experience in data engineering and / or analysis.