{"id":163911,"url":"https://alion.io/job/dvt-data-engineering-lead-data-science-and-ai","title":"Data Engineering Lead – Data Science and AI","company":{"id":57384,"name":"DVT","domain":"dvt.co.za","url":"https://alion.io/company/dvt","size_band":"201-500","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Recruitee","truth_index":{"grade":"A","score":88,"open_postings":4,"ghost_share":0,"stale_share":0.5,"repost_share":0,"time_to_fill_p50_days":55,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":"contractor","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Johannesburg, South Africa"],"countries":["ZA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":46000,"max_usd":105000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":662},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Feature Store","optional":false},{"name":"FinOps","optional":false},{"name":"Git","optional":false},{"name":"Incident Management","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-08-26T07:28:00Z","employer_posted_date":"2026-08-26","last_verified_at":"2026-10-17T18:10:34Z","board_verified":true,"closed_at":null,"days_open":52,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":52},"description":"DVT is a leading technology consulting and software engineering company delivering innovative solutions across Africa and internationally. We partner with clients to solve complex business challenges through software engineering, cloud platforms, data, artificial intelligence, and digital transformation. Our teams combine deep technical expertise with a strong consulting mindset to create measurable business value.\nOur Data Practice is looking for an experienced Data Engineering Lead to design, build and govern the data and technology architecture underpinning our Data Science, Machine Learning, Generative AI and agentic AI initiatives. You will provide the engineering capability required to move analytical and AI solutions from experimentation into secure, scalable, production-ready services.\nThis hands-on technical leadership role combines architecture ownership, engineering delivery and coordination of engineering resources, with a core focus on establishing the Azure-based architecture used by the team, including governed data pipelines between our AWS data environment and Azure-based Data Science and AI platforms.\nRequirements\nKey Responsibilities:\nDefine and maintain the target data engineering architecture for Data Science and AI workloads, including data preparation, model deployment, GenAI applications and agentic workflows.\n\nDesign the architecture and integration patterns for bringing data from AWS into the Azure Data Science environment, working with IT, Data Platform, Cloud and Security teams.\n\nOwn data engineering delivery, building reusable pipelines, transformations and curated datasets, and standardised frameworks for ingestion, transformation, orchestration and publishing.\n\nDefine the approach to reusable features and data products, including feature-store capabilities, lineage, versioning and monitoring.\n\nPartner with Data Scientists and Engineers to establish production-grade MLOps and LLMOps capabilities, including model deployment, versioning, monitoring and retraining.\n\nProvide the data engineering foundations for Generative AI and agentic AI solutions, including ingestion, chunking, indexing and governance of enterprise information.\n\nEnsure data and AI solutions align with governance, privacy, responsible AI, security and data quality standards.\n\nProvide technical leadership to Data Engineers supporting the Data Science portfolio, and translate the roadmap into a prioritised engineering and architecture plan.\n\nEstablish monitoring, operational support, incident management and cost-optimisation practices, and act as primary technical liaison with architecture, infrastructure, cybersecurity and governance teams.\n\nEssential Experience & Qualifications Required\nProven, senior-level experience (7+ years) in data engineering, architecture, and cloud platforms.\n\nDegree in Computer Science, Information Systems, Data Engineering, Software Engineering, Mathematics or a related field.\n\nMicrosoft Azure and/or AWS architecture or engineering certifications advantageous.\n\nStrong practical experience with Microsoft Azure data and AI services (e.g. Azure Data Factory, Azure Functions, Azure Storage, Azure Machine Learning), and experience integrating data across AWS and Azure environments.\n\nExperience building and operating production data pipelines (batch, incremental, streaming or API-based), with data orchestration, automated testing, monitoring and deployment practices.\n\nExperience supporting Data Science, machine learning or AI teams, including implementing MLOps or model deployment capabilities.\n\nStrong Python and SQL skills, with experience in data modelling and transformation frameworks.\n\nExperience with Git-based source control, CI/CD pipelines and Infrastructure as Code.\n\nExperience working with data governance, information security and enterprise architecture teams, and leading technical delivery or coordinating engineers.\n\nAdvantageous Experience\nExperience with Microsoft Fabric, Synapse Analytics or Databricks.\n\nExperience with AWS services such as S3, Glue, Athena, Redshift, Lambda or SageMaker.\n\nExperience building or supporting feature stores, model registries and experiment-tracking platforms.\n\nExperience with containerisation, orchestration technologies, and relational, document, vector or analytical databases.\n\nExposure to FinOps and cloud cost optimisation practices.\n\nImportant to Know\nThis is a hands-on Data Engineering and Cloud Architecture leadership role embedded within the Data Science and AI function, not a pure infrastructure or platform-operations role. The focus is establishing the data architecture, pipelines and engineering foundations that enable Data Science, ML and AI delivery.","description_format":"text","description_chars":4707,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","IT Consulting & Digital Transformation","Software Testing & QA","Custom Software Development"],"lifecycle":[{"event":"open","at":"2026-08-26T07:28:00Z"}],"visa":[],"liveness":{"score":60,"band":"ok","label":"Likely open","p_open":1,"p_active":0.8,"p_room":0.75,"age_days":51,"expected_fill_days":55,"reasons":["conf:0","velocity","win:late"],"computed_at":"2026-10-17T05:46:00Z"},"pay":null,"html_url":"https://alion.io/job/dvt-data-engineering-lead-data-science-and-ai","json_url":"https://alion.io/job/dvt-data-engineering-lead-data-science-and-ai.json","meta":{"generated_at":"2026-10-17T19:50:09Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":3341,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":57384},"rest":"https://alion.io/mcp/rest/get_company?id=57384"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fdvt-data-engineering-lead-data-science-and-ai"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fdvt-data-engineering-lead-data-science-and-ai"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fdvt-data-engineering-lead-data-science-and-ai"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/dvt-data-engineering-lead-data-science-and-ai\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fdvt-data-engineering-lead-data-science-and-ai"}]}