{"id":1108148,"url":"https://alion.io/job/indicium-com-data-engineer-senior-consultant","title":"Senior Data Engineer","company":{"id":678451,"name":"Indicium","domain":"indicium.com","url":"https://alion.io/company/indicium","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"C","score":58,"open_postings":27,"ghost_share":0.704,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-14T06:34:16Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","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":99000,"max_usd":192000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":35},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Anthropic","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Bicep","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Dagster","optional":false},{"name":"Databricks","optional":false},{"name":"Flink","optional":false},{"name":"GCP","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI","optional":false},{"name":"Pulumi","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Great Expectations","optional":true}],"status":"live","first_seen_at":"2026-09-21T16:11:38Z","employer_posted_date":"2026-09-22","last_verified_at":"2026-10-14T04:55:29Z","board_verified":true,"closed_at":null,"days_open":22,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":22},"description":"Data Engineer | Senior Consultant\nLondon\nAbout Indicium AI\nIndicium AI is trusted by the world's leading enterprises to deliver AI and data into production at scale. We are a global AI-native consultancy with proven experience across Financial Services, Energy & Utilities, Healthcare & Life Sciences, Retail & CPG, and Manufacturing. From strategy, to build, to business outcomes, we unlock value from data and AI with unmatched clarity, speed, and capability.\nPowered by 600+ data, engineering, and AI experts serving 50+ enterprise clients from 5 global locations, we work side-by-side with top partners including Databricks, Snowflake, AWS, Microsoft, Google Cloud, Anthropic, and OpenAI to deliver transformative data and AI solutions that drive measurable business impact.\nOverview\nWe're seeking an experienced Senior Data Engineer to design, build, and scale modern cloud-native data platforms that enable advanced analytics, AI, and business-critical decision making.\nThis role is ideal for someone who enjoys solving complex data challenges end-to-end, from architecting platforms and pipelines through to enabling AI-ready data products. You'll work closely with clients to modernise their data estates, implement best-in-class engineering practices, and deliver scalable data solutions across a variety of cloud environments and technologies.\nAs a consultant, you'll combine deep technical expertise with a pragmatic, outcome-focused mindset, helping enterprise organisations turn their data strategies into reality while influencing engineering best practices across delivery teams.\nResponsibilities\nDesign and implement modern data platforms, data products, and scalable data pipelines across cloud environments.\nBuild, optimise, and maintain batch and real-time data processing solutions to support analytics, reporting, machine learning, and AI use cases.\nWork with clients to understand business requirements and translate them into robust technical solutions.\nContribute to solution architecture, platform design, and technology selection decisions.\nImplement software engineering and DataOps best practices including testing, observability, CI/CD, version control, and infrastructure automation.\nDevelop and optimise data models, transformations, and storage layers to ensure performance, reliability, and scalability.\nCollaborate with cross-functional teams including Data Scientists, AI Engineers, Platform Engineers, Architects, and business stakeholders.\nSupport clients through discovery, design, delivery, and adoption phases of data transformation programmes.\nMentor engineers and contribute to the growth of engineering capability across project teams.\nContribute to internal initiatives including accelerators, technical communities, blogs, thought leadership, and capability development.\nRequired Skills & Experience\nStrong hands-on experience building modern data platforms and data products in enterprise environments.\nProven experience with one or more major cloud platforms including AWS, Azure, or Google Cloud Platform.\nProven commercial experience with Databricks and/or Snowflake, including the design, implementation, and optimization of data platforms at scale\nStrong SQL expertise and software engineering experience using Python and/or other modern programming languages.\nExperience developing and orchestrating data pipelines using technologies such as DBT, Apache Spark, Airflow, Dagster, Kafka, Flink, or equivalent tooling.\nSolid understanding of data lakehouse, warehouse, and medallion architecture patterns.\nExperience applying DevOps and DataOps best practices including CI/CD, automated testing, monitoring, observability, and release management.\nExperience with Infrastructure as Code technologies such as Terraform, Pulumi, CloudFormation, or Bicep.\nStrong understanding of distributed systems, data modelling, data governance, security, and performance optimisation.\nAbility to engage with technical and non-technical stakeholders, communicating complex concepts in a clear and pragmatic way.\nExperience working within consulting, professional services, or client-facing delivery environments.\nNice to Have\nExperience building AI-ready data platforms and supporting GenAI, ML, or advanced analytics workloads.\nExperience with real-time streaming architectures and event-driven systems.\nExperience with data mesh, data product operating models, or modern data governance frameworks.\nExposure to Data Quality and Observability platforms such as Great Expectations, Monte Carlo, or Soda.\nIndustry experience within Financial Services, Energy & Utilities, Healthcare, Manufacturing, or Retail.\nCloud provider and/or platform certifications across AWS, Azure, GCP, Databricks, or Snowflake.\nWhy Indicium AI\nFast-growing global AI and Data consultancy with significant opportunities for career progression.\nWork on high-impact transformation programmes with some of the world's leading enterprises.\nCompetitive salary and performance-based bonus structure.\nAccess to leading technologies and strategic partnerships across the AI and Data ecosystem.\nCollaborative, low-ego culture where expertise, curiosity, and innovation are valued.\nChoose your own equipment, including MacBook, PC, and accessories.\nDedicated learning and development budget to support certifications and continuous growth.\nOpportunity to shape the future of a rapidly growing AI-native consultancy.","description_format":"text","description_chars":5414,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Apple Macbook"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["AI Consulting & Integration","Analytics & BI Consulting","Data Engineering & Migration Services"],"lifecycle":[{"event":"open","at":"2026-09-22T07:58:19Z"}],"visa":[],"liveness":{"score":53,"band":"ok","label":"Likely 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