{"id":2458124,"url":"https://alion.io/job/deloitte-manager-senior-databricks-technical-lead-solution-architect","title":"Manager, Senior Databricks Technical Lead & Solution Architect","company":{"id":272,"name":"Deloitte","domain":"deloitte.com","url":"https://alion.io/company/deloitte","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Avature","truth_index":{"grade":"B","score":80,"open_postings":10,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":16,"computed_at":"2026-10-13T05:45:00Z"}},"role":"Solutions","role_family":"Solutions","seniority":"lead","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":79000,"max_usd":146000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":50},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"Airflow","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-13T16:35:18Z","employer_posted_date":"2026-10-13","last_verified_at":"2026-10-13T16:35:18Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Connect to your Industry\nDo you want to lead the engineering delivery and shape the solution architect of some of the UK's largest and most ambitious Data & AI programmes?\nWithin Technology & Transformation organisations are increasingly relying on modern data platforms and AI to accelerate innovation, improve decision-making, and unlock new business value. As a Senior Databricks Data & AI Engineer / Technical Lead, you'll provide the technical leadership that enables these transformations-leading engineering teams, shaping solution architecture, and delivering enterprise-scale data, machine learning, and AI solutions on the Databricks Data Intelligence Platform.\nWorking alongside some of the industry's leading architects, engineers, and AI specialists, you'll help clients build secure, scalable, and high-performing data and AI platforms that power the next generation of intelligent applications.\nConnect to your career at Deloitte\nDeloitte drives progress. Using our vast range of expertise, we help our clients' become leaders wherever they choose to compete. To do this, we invest in outstanding people. We build teams of future thinkers, with diverse talents and backgrounds, and empower them all to reach for and achieve more.\nWhat brings us all together at Deloitte? It’s how we approach the thousands of decisions we make every day. How we behave, our beliefs and our attitudes. In other words: our values. Whatever we do, wherever we are in the world, we lead the way, serve with integrity, take care of each other, foster inclusion, and collaborate for measurable impact.These five shared values lead every decision we make and action we take, guiding us to deliver impact how and where it matters most.\nConnect to your opportunity\nWe're expanding our Databricks Engineering practice and are looking for experienced technical leaders who combine deep engineering expertise, solution architecture capability with strong delivery leadership. You'll work alongside exceptional data, AI, and cloud specialists to design, build, and deliver complex enterprise solutions while leading distributed engineering teams and shaping technical direction across multiple workstreams.\nDepending on your strengths and client needs, you may focus more on hands-on engineering leadership and delivery, end-to-end solution and platform architecture, or a combination of both across enterprise Databricks transformation programmes. The ideal candidate will possess extensive hands-on expertise across the Databricks Lakehouse Platform, modern data engineering, machine learning, and Generative AI, while providing technical leadership, design authority, and engineering governance throughout the delivery lifecycle.\nAs a key member of our team, you will:\nLead the technical delivery and/or solution architecture of enterprise-scale Databricks Data & AI implementations from solution design through to production deployment.\nAct as the technical lead and design authority across multiple workstreams, ensuring solution quality, scalability, security, and alignment with engineering best practices.\nLead and mentor onshore and offshore engineering teams, fostering technical excellence, collaboration, and continuous improvement.\nDrive engineering delivery by establishing technical standards, reviewing solution designs, managing technical risks, and ensuring successful execution against project objectives.\nConduct code reviews and engineering quality assurance, promoting clean, maintainable, high-quality code and adherence to software engineering best practices.\nOptimise platform performance across Spark workloads, Delta Lake, data pipelines, storage, and compute to maximise scalability, reliability, and cost efficiency.\nDesign and deliver enterprise-grade Machine Learning, Generative AI and Agentic AI solutions leveraging the Databricks Data Intelligence Platform, MLflow, Mosaic AI, Vector Search, and modern LLM capabilities where appropriate.\nPartner with solution architects, product owners, client stakeholders, and engineering teams to translate business requirements into scalable technical solutions.\nCoach and develop engineers through technical mentoring, knowledge sharing, and establishing reusable engineering frameworks and best practices.\nOwn technical governance by maintaining engineering standards, architectural integrity, documentation, and design decisions throughout project delivery.\nDefine enterprise solution and platform architectures on Databricks - producing reference architectures, blueprints, and target-state designs that span data engineering, ML, and Generative AI.\ndelivery, and advising client leadership on architecture strategy, platform roadmaps, and target operating models.\nConnect to your skills and professional experience\nOverall, you're an inspiring technical leader, an experienced engineer, and a delivery-focused problem solver. You understand that successful programmes are built on strong technical leadership, engineering excellence, and collaborative teams.\nYou're passionate about mentoring others, making sound architectural decisions, and delivering innovative Data & AI solutions that create measurable business value.\nYou'll have strong technical skills including some or all of the following:\nExtensive experience delivering enterprise-scale Data Engineering and AI solutions using the Databricks Data Intelligence Platform.\nProven experience as a solution or platform architect, defining reference architectures, integration patterns, and target-state designs across enterprise Databricks environments.\nDeep expertise across Databricks including Delta Lake, Unity Catalog, Spark, PySpark, Databricks SQL, Databricks Workflows, Lakeflow, Lakehouse architecture, MLflow, AI/BI Genie, Mosaic AI, and Agent Bricks.\nProven experience leading engineering teams across both onshore and offshore delivery models.\nStrong experience establishing engineering standards, technical governance, and design authority across large programmes.\nExpertise in software engineering best practices including Git, CI/CD, automated testing, Infrastructure as Code, and peer code reviews.\nStrong experience designing, implementing and optimising large-scale batch and streaming data pipelines.\nAdvanced Spark performance tuning and optimisation experience across storage, compute, and workload execution.\nExperience delivering production Machine Learning solutions using MLflow, feature engineering, model lifecycle management, and MLOps principles.\nExperience designing and delivering enterprise AI solutions, with deep expertise in Agentic AI architectures, AI Agents, Retrieval-Augmented Generation (RAG), Vector Search, LLM orchestration, prompt engineering, AI governance and responsible AI practices.\nExcellent communication and stakeholder management skills, with the ability to influence technical and non-technical audiences alike.\nExperience working across Azure, AWS, or GCP cloud ecosystems.\nEssential:\nProven experience leading enterprise-scale Databricks implementation programmes.\nExtensive experience acting as a Technical Lead, Engineering Lead, Solution/Platform Architect, or Technical Design Authority, with responsibility for architecture, solution governance, and technical decision making.\nDemonstrable experience leading offshore engineering teams.\nStrong hands-on expertise in Python, PySpark, and SQL.\nExperience designing & delivering enterprise Generative AI & Agentic AI solutions including AI Agents, RAG, Vector Search, LLM Orchestration and AI governance.\nExperience designing & delivering production-grade Machine Learning solutions.\nProven experience conducting solution design reviews, architecture governance, and code reviews.\nStrong understanding of modern software engineering and DevOps practices.\nExperience working within Agile delivery methodologies.\nDeep expertise in the Databricks Data Intelligence Platform, including Apache Spark, PySpark, Delta Lake, Unity Catalog, Databricks SQL, Lakeflow, Mosaic AI ,AI/BI Genie and Agent Bricks. \nStrong experience designing and delivering production-grade batch and streaming data pipelines using modern Databricks engineering patterns. \nAdvanced knowledge of Spark performance tuning, workload optimisation and Databricks platform cost optimisation. \nStrong understanding of Databricks governance, security, enterprise platform architecture, and multi-workspace operating models including Unity Catalog. \nExperience implementing CI/CD, automated testing and deployment practices for Databricks, including Infrastructure as Code and Databricks Asset Bundles. \nExperience enabling ML and Generative AI workloads using MLflow, Mosaic AI and associated Databricks capabilities.\nPreferred:\nDatabricks Machine Learning Engineer or Generative AI certifications. Databricks Certified Data Engineer Professional (or equivalent advanced Databricks certification).\nExperience with Azure DevOps, GitHub Actions, or equivalent CI/CD tooling.\nExperience designing and delivering scalable, production-grade batch and streaming data pipelines on Databricks, including orchestration and integration with enterprise data sources. \nExperience optimising and operationalising data pipelines for performance, reliability and cost, including CI/CD, automated testing and monitoring.\nExperience with orchestration technologies such as Azure Data Factory, Airflow, or Databricks Workflows.\nExperience with Docker, Kubernetes, and containerised deployments.\nConsulting experience delivering complex Data & AI engagements across multiple industries.\nConnect to your business - Technology and Transformation\nDistinctive thinking, deep expertise, innovation and collaborative working. That’s what connects us. That’s what makes us Deloitte. If you want to help solve some of the biggest tech and transformational challenges around, join us. Together, we’ll make an impact that matters.\nEngineering, AI and Data\nWe lead transformation at the heart of our clients; re-engineering the core of our clients’ organisations, helping to unleash growth, and creating better futures for their customers, citizens and employees.\nPersonal independence\nRegulation and controls are standard practice in our industry and Deloitte is no exception. These controls provide important legal protection for both you and the firm. We are subject to a number of audit regulations, one of which requires that certain colleagues abide by specific personal independence constraints (e.g., in relation to any financial interests and employment relationships). This can mean that you and your \"Immediate Family Members\" are not permitted to hold certain financial interests (shares, funds, bonds etc.) with audit clients of the firm, and also prohibitions on certain employment relationships (e.g., you are not permitted to hold a secondary employment role with SEC audit clients of the firm whilst being employed by the firm). The recruitment team will provide further detail as you progress through the recruitment process or you can contact the Independence team upon request.\nConnect with your colleagues\n“The great culture, flexibility, and range of experiences that Deloitte offers is what sets this firm apart. In Technology & Transformation, Deloitte is far ahead of any of our immediate competitors.” - Sophia, Technology & Transformation\n“What attracted me to Deloitte were the endless opportunities and the collective experience of other like-minded individuals. Deloitte’s clients include many of the world’s largest organisations; I wanted to be part of a team that made a difference that I could be proud of.” - Dan, Technology & Transformation\nOur hybrid working policy\nYou’ll be based in London with hybrid working.\nAt Deloitte we understand the importance of balancing your career alongside your home life. That’s why we’ll support you to work flexibly through our hybrid working policy. 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