{"id":1596919,"url":"https://alion.io/job/svitla-systems-middle-data-ai-support-engineer","title":"Middle Data & AI Support Engineer","company":{"id":2216,"name":"Svitla Systems","domain":"svitla.com","url":"https://alion.io/company/svitla-systems","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"A","score":93,"open_postings":7,"ghost_share":0,"stale_share":0.286,"repost_share":0,"time_to_fill_p50_days":55,"computed_at":"2026-10-04T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":[],"countries":[],"hiring_countries":["GB"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":92000,"max_usd":225000,"period":"year","method":"global_role_seniority_cell","sample_n":585},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"ITIL","optional":false},{"name":"Python","optional":false},{"name":"ServiceNow","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-09-25T15:43:19Z","employer_posted_date":"2026-09-25","last_verified_at":"2026-10-05T02:10:43Z","board_verified":true,"closed_at":null,"days_open":9,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":9},"description":"Svitla Systems Inc. is looking for a Middle Data and AI Support Engineer for a full-time position (40 hours per week) in Mexico. Our client is a global, science-led biopharmaceutical company specializing in discovering, developing, and commercializing prescription medicines. The company operates in several therapeutic areas, including oncology, cardiovascular, renal, metabolic, respiratory, immunology, and rare diseases. They work alongside the world's leading academic and biotech research institutions to stimulate innovation and evaluate emerging technologies. The client operates in over 100 countries, and its innovative medicines are used by millions of patients worldwide. The headquarters is located in Cambridge, United Kingdom. This location aligns with the focus on science and innovation, providing proximity to leading academic and research institutions.\nThe Critical Operations team is responsible for keeping US Market data accurate, reliable, and available to business users across areas such as samples, calls, medications, products, and sales.\nAs a Data Support Engineer, you will provide production support for data pipelines, monitoring Airflow DAGs, SnapLogic pipelines, and Databricks jobs, investigating data issues, and managing incidents, service requests, and problem records. The role focuses on hands-on data investigation, SQL-based validation, documented recovery procedures, and effective issue escalation within defined SLAs.\nRequirements\n3+ years of experience providing production support for data pipelines or ETL processes, working within SLAs in a shift-based or follow-the-sun support model.\nHands-on experience investigating data issues end-to-end, from source or vendor files through ingestion, transformation, and loading to published tables or reports.\nAdvanced SQL skills for data analysis and reconciliation, including joins, CTEs, window functions, row-count reconciliation, and identifying missing or duplicate loads.\nProduction experience with Apache Airflow, including monitoring DAG runs, reading task logs, and interpreting Python tracebacks.\nHands-on experience with a cloud data platform, preferably Databricks or Snowflake; experience with Amazon Redshift or an equivalent platform is also considered.\nExperience handling incidents, service requests, and problem records within an ITIL-based process and defined SLAs.\nAbility to document investigation findings clearly, identify the appropriate resolver team, and provide evidence to support escalation.\nAbility to work independently within documented recovery procedures and escalate issues that require further technical intervention.\nWorking English, with the ability to communicate effectively during daily handovers with the team in India.\nWill be a plus\nExperience with Databricks, including job runs, Delta tables, and Databricks SQL.\nExperience with Snowflake and Amazon Redshift.\nExperience with SnapLogic or a similar ETL tool.\nExperience working with AWS S3.\nProactive use of AI tools for troubleshooting, SQL analysis, and technical documentation.\nBasic Python skills for troubleshooting data pipelines.\nExperience with ServiceNow.\nPharmaceutical industry experience, ideally involving US commercial data such as IQVIA data, CRM calls, and samples.\nResponsibilities\nMonitor Airflow DAG runs, SnapLogic pipelines, and Databricks jobs during the assigned shift.\nInvestigate pipeline failures by identifying the failing step in logs, checking source file availability in S3, and validating data freshness using SQL.\nPrioritize incidents based on business impact when multiple pipelines fail simultaneously.\nExecute documented recovery procedures from established runbooks without making code changes.\nEscalate issues that cannot be resolved through documented recovery procedures to the appropriate resolver group, providing the relevant evidence and investigation findings.\nValidate data loads using SQL in Databricks, Amazon Redshift, and Snowflake, including row counts by period, missing periods, and duplicate records.\nManage incidents, service requests, and problem records in ServiceNow within defined SLAs.\nKeep requesters informed throughout the resolution process and document resolution details according to team standards.\nProvide written handovers to the team in India, including open issues, actions taken, and pending decisions.\nDocument new failure patterns in the relevant runbook or knowledge base and flag recurring issues for further investigation.","description_format":"text","description_chars":4484,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"All levels","optional":false}]},"benefits":[],"hiring_locations":[{"name":"United Kingdom","iso":"GB","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["DevOps & Platform Engineering","IT Outsourcing & Dedicated Teams","Custom Software Development"],"lifecycle":[{"event":"open","at":"2026-10-01T18:15:47Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"Filed H-1B visas in the last two years","filings_12m":0,"filings_prev_12m":1,"green_card_filings_12m":0,"median_offered_wage_usd":null,"route":null,"cap_exempt":false,"checked_at":"2026-10-03T21:08:04+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)"],"filings_for_role_12m":0}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":8,"expected_fill_days":55,"reasons":["conf:0","velocity","win:early","comp:brand"],"computed_at":"2026-10-04T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/svitla-systems-middle-data-ai-support-engineer","json_url":"https://alion.io/job/svitla-systems-middle-data-ai-support-engineer.json","meta":{"generated_at":"2026-10-05T02:48:30Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":3860,"day_limit":5000,"remaining_today":1140,"minute_limit":60,"resets_at":"2026-10-06T00:00:00Z"}}}