{"id":3795521,"url":"https://alion.io/job/bridge-next-data-platform-engineer","title":"Data Platform Engineer","company":{"id":2442558,"name":"Bridge Next","domain":"bridgenext.com","url":"https://alion.io/company/bridgenext","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"iCIMS","truth_index":null},"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":["Argentina"],"countries":["AR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Azure","optional":true}],"status":"live","first_seen_at":"2026-11-05T09:15:45Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-06T18:23:23Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Company Overview\nAt Bridgenext, we engineer Growth Operating Systems. Most enterprises have spent millions on their revenue stack and still aren't seeing the growth they expected.They have tools that function, but no system that wins. We help growth-hungry companies close that gap by turning fragmented platforms, siloed teams, and disconnected data into one integrated Growth OS. More than a technology company or marketing agency, we're a global digital consultancy with experts in engineering, data, AI, creative and more.\nOur teams are made up of experts who believe in engineering impact, starting with putting people at the center of everything we do. Every team member directly shapes our work, culture, and values. Nothing matters more to us than a kind, respectful, fulfilling environment that supports everyone. Our flexible, inclusive culture gives you the autonomy, resources, and opportunities to thrive.\nPosition Description\nWe are looking for DataOps engineer with hands-on experience to automate our Databricks Jobs/Workflows, DLT, and SQL tasks, implement and operate Unity Catalog at scale.\nKey Responsibilities:\nAutomation & Orchestration (Jobs/Workflows & CI/CD)Design, build, and maintain Databricks Workflows/Jobs (multi-task graphs, retries, triggers, alerts) for batch, and SQL workloads. \nImplement CI/CD pipelines (GitHub Actions/Azure DevOps/GitLab): plan/apply for IaC, validate job JSON, environment promotion, approvals, and rollback. \nBuild templates, parameterized job definitions (ingestion/batch/streaming/SQL) with standardized logging, notifications, and governance. \nEnforce run-as service principals, job versioning, change auditability, and artifact immutability. \nAutomate provisioning via Terraform (Databricks provider), Databricks SDK (Python/Go), and REST API 2.1 for Jobs, DLT, Repos, SQL Warehouses, and Unity Catalog. \n\nUnity Catalog - Automation, Governance & MigrationCatalog & Schema Provisioning (Automation-first): Idempotent creation of catalogs, schemas, default locations, owners, grants, volumes, storage credentials, and external locations using Terraform/SDK/REST. \nGrant-as-Code: Standardize RBAC with templates (OWNERSHIP, USE CATALOG/SCHEMA, SELECT, MODIFY, CREATE, READ/WRITE FILES); integrate SCIM groups and service principals. \nSecurity & Audit: Dynamic views for row/column-level security, data classification tags, audit logging, token policies, periodic permissions drift detection & remediation. \nDelta Sharing: Automate providers/recipients, share objects, and scheduled access reviews/expiry. \nUnity Catalog Migration (HMS → UC or multi-workspace to UC): discovery, wave planning, external/managed table registration, permission model migration, dual-run validation (row counts, schema parity, query replay), cutover & rollback. \n\nReliability & Data QualityDefine SLOs for pipeline success, latency, and data freshness; drive ≥99% T1 success and low MTTR. \nImplement data quality checks (DLT expectations, dbt-expectations/GX), idempotency, schema evolution strategy, checkpointing & replay. \nBuild incident response playbooks; lead RCAs and preventative actions. \n\nMust Have Skills:\n5-8 years of experience in data engineering, platform engineering, or cloud infrastructure roles.\nStrong hands-on experience with Databricks administration (workspace management, cluster policies, access controls, cost optimization).\nWorking knowledge of Databricks workflow development (job orchestration, scheduling, pipeline monitoring).\nProficiency in Terraform for infrastructure as code and automated provisioning.\nSolid experience with AWS cloud services and architecture.\nGood Python scripting skills for automation and tooling.\nGood understanding of CI/CD practices and version control (Git).\nExposure to or experience implementing Agentic AI solutions, Genie spaces and apps primarily or anything similar.\nProfessional Skills:\nStrong problem-solving skills and ability to work in a collaborative, fast-paced environment.\nExcellent English communication skills\nBridgenext is an Equal Opportunity Employer","description_format":"text","description_chars":4069,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[{"language":"English","level":"Upper-Intermediate (B2)","optional":false}]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Blockchain & Crypto","Digital Goods","Data Engineering & Migration Services"],"lifecycle":[{"event":"open","at":"2026-11-05T09:15:45Z"}],"visa":[],"liveness":{"score":99,"band":"hot","label":"Hiring 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