{"id":1875099,"url":"https://alion.io/job/mercedes-benz-adas-data-analytics-engineer","title":"ADAS Data & Analytics Engineer","company":{"id":136,"name":"Mercedes-Benz","domain":"mercedes-benz.com","url":"https://alion.io/company/mercedes-benz","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career sitemap","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":16500,"max_usd":40000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":15},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Flyte","optional":false},{"name":"GCP","optional":false},{"name":"Grafana","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-09-28T00:00:00Z","employer_posted_date":"2026-09-28","last_verified_at":"2026-10-12T02:45:29Z","board_verified":true,"closed_at":null,"days_open":14,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":14},"description":"Aufgaben\n Job Description - ADAS Data & Analytics Engineer (4-7 Years)\nRole Overview\nWe are looking for a Data & Analytics Engineer with 4-7 years of experience to work on ADAS validation, data processing, and analytics workflows. The role involves handling large-scale vehicle data, building automation pipelines, and generating insights to support decision-making.\nKey Responsibilities\nData Processing & Analysis\nWork with ADAS/event-based datasets from multiple sources (signals, logs, video-derived data)\nPerform data extraction, cleaning, and transformation using Python\nAnalyze time-series data and derive meaningful insights for validation use cases\nAutomation & Workflow Development\nDevelop scripts and workflows for automated data processing and reporting\nIdentify opportunities to automate repetitive analytics tasks using ML or rule-based logic\nWork with orchestration tools (Airflow/Flyte or similar) for pipeline execution\nData Engineering & Cloud\nHandle large datasets (e.g., Parquet) and optimize data pipelines for performance\nWork with cloud platforms (preferably GCP/AWS) for data storage and processing\nIntegrate APIs and databases for data access and processing\nVisualization & Reporting\nBuild dashboards using Power BI / Tableau / similar tools\nDesign KPIs and visualize insights for stakeholders\nEnsure clear and structured storytelling of data insights\nCollaboration & Domain Work\nWork closely with validation teams and SMEs to understand data requirements\nSupport ADAS function analysis and validation workflows\nContribute to continuous improvement of analytics use cases\nRequired Skills\nTechnical Skills\nStrong Python skills (Pandas, NumPy, data processing)\nGood SQL knowledge (RDBMS/NoSQL basics)\nExperience with large-scale data handling and processing\nExposure to cloud environments (GCP/AWS preferred)\nKnowledge of dashboarding tools (Power BI/Grafana/Tableau)\nGood to Have\nExperience in ADAS / automotive domain\nUnderstanding of time-series data & signal processing\nExposure to ML basics (classification, model usage)\nKnowledge of containerization (Docker/Kubernetes)\nQualifications\nBachelor’s/Master’s in Computer Science, Electronics, or related field\n4-7 years of relevant experience in Data Analytics / Data Engineering\nBehavioral Expectations\nStrong analytical and problem-solving skills\nAbility to work in a dynamic environment\nGood collaboration and communication skills\nStructured thinking and ownership mindset\nQualifikationen\n Job Description - ADAS Data & Analytics Engineer (4-7 Years)\nRole Overview\nWe are looking for a Data & Analytics Engineer with 4-7 years of experience to work on ADAS validation, data processing, and analytics workflows. The role involves handling large-scale vehicle data, building automation pipelines, and generating insights to support decision-making.\nKey Responsibilities\nData Processing & Analysis\nWork with ADAS/event-based datasets from multiple sources (signals, logs, video-derived data)\nPerform data extraction, cleaning, and transformation using Python\nAnalyze time-series data and derive meaningful insights for validation use cases\nAutomation & Workflow Development\nDevelop scripts and workflows for automated data processing and reporting\nIdentify opportunities to automate repetitive analytics tasks using ML or rule-based logic\nWork with orchestration tools (Airflow/Flyte or similar) for pipeline execution\nData Engineering & Cloud\nHandle large datasets (e.g., Parquet) and optimize data pipelines for performance\nWork with cloud platforms (preferably GCP/AWS) for data storage and processing\nIntegrate APIs and databases for data access and processing\nVisualization & Reporting\nBuild dashboards using Power BI / Tableau / similar tools\nDesign KPIs and visualize insights for stakeholders\nEnsure clear and structured storytelling of data insights\nCollaboration & Domain Work\nWork closely with validation teams and SMEs to understand data requirements\nSupport ADAS function analysis and validation workflows\nContribute to continuous improvement of analytics use cases\nRequired Skills\nTechnical Skills\nStrong Python skills (Pandas, NumPy, data processing)\nGood SQL knowledge (RDBMS/NoSQL basics)\nExperience with large-scale data handling and processing\nExposure to cloud environments (GCP/AWS preferred)\nKnowledge of dashboarding tools (Power BI/Grafana/Tableau)\nGood to Have\nExperience in ADAS / automotive domain\nUnderstanding of time-series data & signal processing\nExposure to ML basics (classification, model usage)\nKnowledge of containerization (Docker/Kubernetes)\nQualifications\nBachelor’s/Master’s in Computer Science, Electronics, or related field\n4-7 years of relevant experience in Data Analytics / Data Engineering\nBehavioral Expectations\nStrong analytical and problem-solving skills\nAbility to work in a dynamic environment\nGood collaboration and communication skills\nStructured thinking and ownership mindset","description_format":"text","description_chars":4906,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Automotive Manufacturing","Exhibitions"],"lifecycle":[{"event":"open","at":"2026-10-04T22:02:48Z"}],"visa":[],"liveness":{"score":77,"band":"hot","label":"Hiring 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