Senior SQL & SSIS Data Engineer (Data warehouse)

Adecco; City Of London; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A recruitment consultancy is seeking a Senior SQL & SSIS Data Engineer in London for a 6-month project with potential for permanent placement. The role involves optimizing a SQL Server 2019 data warehouse, managing SSIS batch jobs, and collaborating on a significant migration project. Ideal candidates will have expert SQL skills, strong SSIS experience, and a track record in performance tuning. This position offers a hybrid working model and opportunities for contract extensions based on performance.

Benefits

Hybrid working arrangement

Opportunities for contract extensions based on performance

Qualifications

• Expert-level SQL proficiency in Data Warehousing and PowerBI is essential.
• Strong SSIS development and optimisation experience is essential.
• Deep understanding of execution plans and performance tuning techniques.

Responsibilities

• Analyse and optimise SSIS ETL pipelines and batch jobs.
• Improve SQL performance through effective indexing and execution plans.
• Identify and resolve locking and blocking issues to enhance efficiency.

Skills

Expert-level SQL proficiency

Strong SSIS development and optimisation experience

Solid experience with SSAS and SSRS tools

Deep understanding of execution plans and performance tuning techniques

Strong troubleshooting and problem-solving skills

Proven history of improving complex ETL environments

Tools

SQL Server 2019

PowerBI

Job description

Job Title: Senior SQL & SSIS Data Engineer (Data warehouse)

Contract Length: 6 Months (possibility for perm)

Location: London (5 days in 10)

Working Pattern: Full Time

Rate: Highly competitive rate available for suitable candidates

Are you a data wizard ready to take on a challenging role in a dynamic Data Warehouse team? Our client is on the lookout for a talented Senior Data Engineer with a passion for SQL and SSIS development. Join us for a thrilling 6-month journey focused on optimising our existing SQL Server 2019 data warehouse environment, which is poised for transformation!

About the Role

In this hands‑on, technical position, you will take ownership of a significant portfolio of around 90 SSIS batch jobs. You'll dive deep into performance analysis, tackle existing technical debt, and implement best practises that will elevate our data operations. Your expertise will be crucial as we gear up for an exciting data warehouse migration from New York to London in 2026!

Key Responsibilities

• Analyse and optimise SSIS ETL pipelines and batch jobs.
• Improve SQL performance through effective indexing and execution plans.
• Identify and resolve locking and blocking issues to enhance efficiency.
• Apply best practises to boost overall warehouse performance.
• Work independently to drive optimisation initiatives.
• Collaborate with senior developers for insightful technical reviews.
• Support and prepare for upcoming migration activities.

Required Skills

• Expert‑level SQL proficiency (SQL Server 2019 on‑prem) Data Warehousing and PowerBI is essential
• Strong SSIS development and optimisation experience is essential.
• Solid experience with SSAS and SSRS tools.
• Deep understanding of execution plans and performance tuning techniques.
• Strong troubleshooting and problem‑solving skills.
• Proven history of improving complex ETL environments.

Nice to Have

• Experience with C# for SSIS scripts.
• Proficiency in Python.
• Exposure to Power BI for data visualisation.

Why Join Us?

• Be part of a vibrant team that values innovation and collaboration.
• Contribute to a significant migration project that will make a real impact.
• Enjoy a hybrid working arrangement that promotes work‑life balance.
• Opportunities for contract extensions based on performance.

If you're ready to unleash your data engineering skills and make a meaningful difference, we want to hear from you! Apply today and embark on an exciting journey with us as we transform our data landscape.

Let's shape the future of our data together!

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