Senior Data Engineer

Job Description:

Key Responsibilities

* Conduct a structured assessment of all 106 SSAS tables: identify redundant tables and columns, inefficient source queries, heavy calculations, and partition strategy gaps.

* Audit the full ETL chain (stored procedures on the read replica DW load SSAS re-ETL) and map transformation duplication and dependencies.

* Diagnose and permanently resolve daily SSAS processing failures (memory pressure, timeouts, locking, connectivity, error handling) using Extended Events, SQL Server Profiler traces, msmdsrv logs, and DMVs.

* Redesign the SSAS refresh strategy: implement partitioning and incremental processing to replace the current full daily refresh, targeting a processing window under 30 minutes.

* Optimise SSAS memory usage and model design (column/table pruning, data type and encoding optimisation, relationship and calculation tuning, aggregation strategy, query/storage mode evaluation).

* Refactor and consolidate transformation logic into a single, auditable pipeline; eliminate re-ETL inside SSAS where possible by pushing transformations to the DW layer.

* Redesign the DW load pattern (currently daily full snapshot filtered to current date) toward incremental/delta loads where feasible.

* Perform SQL Server database and query performance optimisation: stored procedure tuning, indexing, statistics, execution plan analysis.

* Implement robust error handling, retry logic, data validation, reconciliation checks, and automated monitoring/alerting for the daily processing chain.

* Work with the client's architects, analysts, and business stakeholders; operate independently against a fixed 2-month timeline.

* Deliver updated architecture documentation, an operational runbook for the SSAS process, and monitoring recommendations; complete structured knowledge transfer before engagement close.

Required Technical Stack

The candidate must have strong hands-on experience with:

SQL Server Analysis Services (SSAS) deep expertise in Tabular (VertiPaq engine internals, partitioning, incremental refresh, processing options, memory management, DAX optimisation) and working knowledge of Multidimensional (MDX, aggregations, processing tuning)

* SSAS troubleshooting tooling: DMVs, Extended Events, Profiler, DAX Studio, Tabular Editor, VertiPaq Analyzer

* Microsoft SQL Server (2016+) database engine, Agent jobs, performance tuning, execution plans, indexing, statistics

* SQL / T-SQL complex stored procedures, views, functions, transformation logic

* SQL Server Integration Services (SSIS) or equivalent orchestration of SQL Server-based ETL

* ETL/ELT design and consolidation – refactoring multi-hop transformation chains

* Data warehousing and dimensional modelling (Kimball), snapshot vs incremental load patterns

* Cross-environment data movement between cloud-hosted SQL Server (AWS RDS or similar) and on-premises SQL Server

* Data validation, reconciliation, error handling, and job monitoring/alerting

* Git / DevOps practices for source control and deployment of database and SSAS artefacts.

only Immediate or serving notice period can apply.