{"id":1539115,"url":"https://alion.io/job/mbrdna-data-engineer-adas-fleet-analytics","title":"Data Engineer ADAS Fleet Analytics","company":{"id":693735,"name":"MBRDNA","domain":"mbrdna.com","url":"https://alion.io/company/mbrdna","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Jose, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":85000,"max_usd":188000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":188},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Delta Lake","optional":false},{"name":"Git","optional":false},{"name":"LLM","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"AWS","optional":true},{"name":"Databricks","optional":true},{"name":"DuckDB","optional":true},{"name":"FastAPI","optional":true},{"name":"Feature Store","optional":true},{"name":"GCP","optional":true},{"name":"Time Series Forecasting","optional":true}],"status":"live","first_seen_at":"2026-09-16T18:01:23Z","employer_posted_date":"2026-09-16","last_verified_at":"2026-10-01T08:41:09Z","board_verified":true,"closed_at":null,"days_open":15,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":15},"description":"Mercedes-Benz uses large-scale vehicle telemetry to evaluate, monitor, and improve its Advanced Driver Assistance Systems. As a Data Engineer on the US ADAS Data & Forensics team, you will build and operate the data pipelines that turn raw vehicle signals into trusted KPIs, fleet dashboards, and campaign-health monitoring for management and the engineers who calibrate ADAS functions. You will own the full data lifecycle, including real-time ingestion, binary protocol decoding, Bronze/Silver/Gold processing with PySpark and Delta Lake, and delivery through APIs and dashboards. You will also manage data campaigns end to end, including VIN enrollment, fleet-health tracking, coverage-gap detection, and the Sold to Consented to Capable to Active vehicle funnel. The architecture is evolving toward applied AI, and you will build the data infrastructure required for vision-language models, LLM-based event classification, embedding retrieval, and model-based event scoring.\nRelocation assistance (domestic or international) is not provided for this position.\nJob Responsibilities:\nDesign and maintain scalable telemetry pipelines using Event Hub, Medallion architecture, Delta Lake MERGE, schema evolution, and blue/green data deployments.\nOwn campaign and fleet management, including enrollment rosters, ingestion-completeness monitoring, VIN reconciliation, and automated coverage alerts.\nDevelop fleet KPIs for engineering, including safety events and takeover analysis; operations, including data freshness and pipeline health; and management, including trends and cohort comparisons.\nBuild ML-ready data infrastructure, including video and signal pipelines for SSR recordings, embedding stores, feature-engineering layers, and model-output integration into Gold.\nOperate the Azure data platform, including ADLS Gen2, Synapse Spark, Event Hub, and Container Apps, and support Terraform-managed infrastructure and CI/CD.\nWrite automated tests, maintain documentation alongside code, and participate in code reviews and incident response.\nMinimum Qualifications:\nBachelor's or Master's degree in Computer Science, Data Engineering, or a related field. Equivalent experience may be considered.\n2-5 years of experience in data engineering or big-data analytics with production pipeline ownership.\nStrong Python, PySpark DataFrame API and performance-tuning skills, and SQL skills including window functions and aggregations.\nExperience with a columnar or transactional data-lake technology such as Delta Lake, Iceberg, Hudi, or managed Parquet.\nExperience with automated testing for data pipelines and Git-based development workflows.\nAbility to diagnose production failures, including schema conflicts, data skew, and memory issues, and communicate trade-offs to technical and non-technical stakeholders.\nPreferred Qualifications:\nStrongly Preferred\nMedallion or other layered data-processing patterns.\n\nCloud data-platform experience in Azure, AWS, or GCP.\n\nParquet schema design and schema evolution.\n\nProduction data-quality practices, including deduplication, idempotency, and data contracts.\n\nTime-series, IoT, or vehicle-telemetry data.\n\nNice to Have\nDuckDB or PyArrow; FastAPI or analytical API delivery; blue/green data deployments.\n\nML data infrastructure, including feature stores, embedding pipelines, vector databases, or video pipelines.\n\nFleet or campaign management for vehicle or IoT programs.\n\nAutomotive data privacy, including CCPA; ADAS or connected-vehicle domain knowledge.\n\nAzure Data Engineer or Databricks certification.\n\nEnglish required; German is an advantage.","description_format":"text","description_chars":3594,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[{"language":"English","level":"All levels","optional":false}]},"benefits":["Relocation assistance"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":true,"industries":["Fleet Management"],"lifecycle":[{"event":"open","at":"2026-09-30T20:15:46Z"}],"liveness":{"score":53,"band":"ok","label":"Likely open","p_open":1,"p_active":0.711,"p_room":0.75,"age_days":14,"expected_fill_days":15,"reasons":["conf:9","win:late","comp:junior"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/mbrdna-data-engineer-adas-fleet-analytics","json_url":"https://alion.io/job/mbrdna-data-engineer-adas-fleet-analytics.json","meta":{"generated_at":"2026-10-01T19:31:53Z","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":2090,"day_limit":5000,"remaining_today":2910,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}