Data.

The Role   You'll own the data lake — the system of record for millions of financial events a day across million of active users. You decide how that data lands, is stored, retained, and governed on S3 + Snowflake/Databricks, so analytics, finance, and regulators all see accurate, reconciled data with zero drift from source.   What you'll be doing ? Own the lakehouse architecture: bronze/silver/gold layers, Iceberg/Delta tables, schema evolution. ? Land operational data via CDC streaming (Kafka, Debezium), handling late and duplicate events. ? Design data layout for speed and cost: partitioning, compaction, file sizing, query performance on Trino/Athena/Snowflake. ? Own retention and archival: storage tiering, regulatory retention, immutability, GDPR deletion. ? Guarantee correctness: freshness SLAs, drift detection, reconciliation against the source wallet and ledger systems. ? Own governance: catalog and lineage, row/column access control, PII masking, encryption, audit trails. ? Monitor ingestion health, data anomalies, and cloud storage/compute spend.   What we're looking for ? 3+ years in data engineering, with real ownership of a large-scale data lake or lakehouse. ? Cloud object storage (S3/GCS) plus Snowflake, Databricks, or BigQuery in production. ? Hands-on with an open table format (Iceberg, Delta, or Hudi). ? Deep understanding of partitioning, file layout, and query optimization at terabyte-plus scale. ? CDC and streaming ingestion experience (Kafka + Debezium or equivalent). ? Strong SQL and data modeling; enough relational grounding to reason about the OLTP systems you capture from — critical for financial ledgers. ? Data lake governance: catalogs, lineage, access control, PII, retention. ? Python and an orchestrator (Airflow/Dagster) as tools — this is an architecture and ownership role, not heads-down coding. ? Nice to have: fintech, iGaming, or another regulated, audit-heavy environment.

Analytics Engineer | £70k–£80k+ | South East London | Hybrid I’m partnering with a fast-scaling digital business that’s investing heavily in data and looking for an Analytics Engineer to play a key role in building out a new data environment. This is a brilliant opportunity for someone who wants more than just maintaining dashboards or existing pipelines. You’ll have real ownership across the full data lifecycle, from APIs and Python pipelines, through to dbt/BigQuery modelling, and finally turning that data into useful insights for the business. They’re looking for someone strong in: Python SQL dbt BigQuery / GCP Looker / Metabase APIs & data pipelines You’ll work directly with the Head of Data, have a huge amount of autonomy, and be trusted to build and improve things rather than just inherit them. Location: South East London Hybrid: 3 days office / 2 days home Salary: £70,000–£80,000+ If you enjoy owning data projects end-to-end and want a role where your work will genuinely shape how the business uses data, I’d love to hear from you.

We are looking for a Senior BI & Analytics Specialist with strong hands-on experience in iGaming / Online Gambling to build and develop the company’s BI and Analytics function. You will work directly with player-level and transactional data across Casino, Sportsbook, CRM, Payments, Marketing, Agents and Finance, turning complex data into actionable business insights. This is not a generic BI role. Strong understanding of iGaming operations, player behaviour, commercial KPIs and profitability is essential. Responsibilities: Build and develop the company’s BI and Analytics structure, including a Single Source of Truth for key KPIs. Develop Power BI dashboards and advanced analysis covering player behaviour, acquisition, retention, churn, LTV, revenue and profitability. Analyse performance across players, brands, markets, channels, agents, products and providers. Analyse the complete player lifecycle, from registration and FTD through retention, reactivation, churn and LTV. Identify trends, anomalies, high-value player segments and growth opportunities. Work closely with Revenue, CRM, Marketing, Operations, Finance and Technology to provide data-driven insights and recommendations. Requirements: 5+ years in BI, Data Analytics or Business Analytics, including at least 2 years in iGaming / Online Gambling. Hands-on experience with player-level and transactional data and a strong understanding of Casino and/or Sportsbook operations. Strong knowledge of iGaming KPIs including GGR, NGR, Turnover, FTD, Active Players, ARPU/ARPPU, Retention, Churn and LTV. Advanced SQL and Power BI, including DAX and Data Modelling. Experience with ETL/ELT, multiple data sources, large datasets and data quality/validation. Ability to connect acquisition, player behaviour, CRM, revenue and costs to understand business performance and profitability. Python, BigQuery/Snowflake/Redshift, APIs and predictive analytics are desirable.