Data Analytics Engineer

Role: Data Engineer

Working Location: Hybrid (1 day per fortnight in Wilmslow office)

The Role

The Citation Group is building out its data and AI capabilities to be best in class. As part of this, we're looking for a Data Migration Engineer to join the data team and support in moving data safely and accurately between systems as we consolidate and modernise our platform landscape.

This isn't a generic ETL role. You'll be working on live migrations between operational systems (CRM, billing, and platform migrations) where the real risk isn't moving the data — it's the things that only surface once it lands: automation overwriting values post-import, subscription or contract logic that doesn't map cleanly, validation rules that silently reject or reshape records. You'll work closely with the Head of Data Migrations, data owners, and platform specialists (Salesforce, Chargebee, Dynamics) to make sure those gaps are found and designed for before cutover, not discovered during UAT.

We're looking for someone who's naturally curious about how systems actually work under the hood — not satisfied with a field-to-field mapping sheet until they understand the logic, constraints, and automation behind both ends of the migration.

Responsibilities

• Lead structured data discovery and profiling at the start of every migration — surfacing quality, completeness, and integrity issues while there's still time to remediate them, and quantifying the remediation effort involved

• Build detailed source-to-target data mappings grounded in a genuine working understanding of both systems — not just field lists, but the underlying logic, constraints, and assumptions each platform makes

• Identify where source and target behave differently (validation rules, required fields, relationship structures, calculated vs. stored values, automation-driven overwrites) during discovery, and design for it rather than letting it surface as a defect in testing

• Build and maintain the ETL/ELT pipelines that move data between systems, including transformation logic for edge cases (e.g. multiple active records per customer, hardcoded vs. derived fields)

• Own reconciliation and validation between source and target post-migration, including tracing discrepancies back to root cause (data issue vs. platform automation vs. mapping error)

• Document migration logic, mapping decisions, and known system quirks so they're reusable across future migrations

• Work with data owners to drive cleanup of quality issues ahead of cutover

• Support cutover planning and execution, including rollback considerations

The Person

We're looking for someone who can roll their sleeves up and dig into both the data and the systems around it. In addition, the successful candidate should have:

• Excellent writing and communication skills with strong attention to detail — you'll need to explain system-behaviour gaps clearly to non-technical stakeholders

• Experience writing, troubleshooting, and debugging advanced SQL queries

• A track record of going beyond field-level mapping to understand why two systems behave differently — validation logic, automation, calculated fields, relationship structures

• Outstanding analytical and problem-solving skills, particularly diagnosing whether an issue is a data problem, a mapping problem, or a platform automation problem

• Experience with ETL/ELT tools and data migration projects specifically (not just general pipeline building)

• Programming experience in Python

• Comfort working with ambiguity — migration requirements shift as discovery uncovers new system behaviour, and you'll need to adapt scope calmly rather than treat it as scope creep

Skills and experience we'd love you to have... but if not? We'll help you get there:

• Experience migrating data into or out of CRM/billing platforms such as Salesforce

• Understanding of how declarative platform automation silently alter data post-import

• Experience in relational cloud-based database technologies like Snowflake, BigQuery, Redshift

• Understanding of cloud computing security concepts

• Familiarity with DBT and Databricks

• Experience working in an agile environment

• Experience working with AI tools (Claude Code, Cortex, etc.) to accelerate migration analysis