{"id":3330932,"url":"https://alion.io/job/mercedes-benz-data-engineering-azure-databricks-power-bi-python","title":"Data Engineering (Azure Databricks, Power BI, Python)","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":{"grade":"A","score":97,"open_postings":52,"ghost_share":0.019,"stale_share":0.058,"repost_share":0.019,"time_to_fill_p50_days":29,"computed_at":"2026-10-30T05:48:23Z"}},"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":["Puchong, Malaysia"],"countries":["MY"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":16500,"max_usd":43000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2679},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Confluence","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GitHub","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Jira","optional":false},{"name":"Microsoft Entra ID","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scrum","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Active Directory","optional":true},{"name":"Delta Lake","optional":true},{"name":"Docker","optional":true},{"name":"FastAPI","optional":true},{"name":"NATS","optional":true},{"name":"PowerShell","optional":true},{"name":"Redis","optional":true},{"name":"Spark","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-27T12:04:24Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-10-30T07:20:30Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Aufgaben\n About Us\nAt Mercedes-Benz, we don’t just build cars, we create great software. We develop tomorrow’s mobility together in our product lines, pushing the digitization of the Mercedes-Benz Group AG forward. As a tech company, we are agile, innovative, and always keep our finger on the pulse of change. This is why inner source, FOSS, secure code, DevOps, infrastructure as code (IaC), data analytics, artificial intelligence, and many more are core components of our daily work.\nIT is our passion, and we move toward a bright future, sometimes quickly, sometimes creatively but always together.\nWe believe in integrity, trust, and transparency as part of our flexible work culture, with a strong emphasis on teamwork and the learning process, making mistakes, and achieving continuous progress together in all products we create and develop within the Mercedes-Benz Group.\nOur workplace is anywhere* with a fast connection whether remotely at home, at your favorite café, or at our integrated office at Wisma Mercedes-Benz, which comes with an LRT station at its doorstep, an al fresco cafeteria, ample greenspaces, and free parking.\nAbout the Role\nWe are looking for an experienced Senior Data Engineer / Data Engineering Lead to join the Sales Planning (Car Sales) function and take a leading role in upcoming data and analytics initiatives.\nThis position combines hands-on data engineering with technical project leadership. The successful candidate will lead the end-to-end delivery of Power BI solutions and Azure-based data pipelines, while coordinating external vendors and working closely with business stakeholders and global teams.\nThe ideal candidate can independently assess technical requirements, define an appropriate solution approach, coordinate delivery, manage stakeholder expectations, and remain hands-on where required.\nKey Responsibilities\nLead the end-to-end delivery of data engineering, data pipeline and Power BI initiatives.\nDesign, develop and maintain scalable solutions using Microsoft Azure, Azure Data Factory and Azure Databricks.\nDevelop, optimize and support data pipelines using SQL and Python.\nWork with Azure Data Lake Storage for data storage, processing and integration requirements.\nDevelop and enhance Power BI reports and dashboards based on business needs.\nCoordinate external vendors and provide technical direction for data engineering activities.\nManage communication and expectations across business stakeholders, technical teams and global counterparts.\nSupport integration requirements involving APIs and multiple data sources.\nApply Azure DevOps Pipelines and/or GitHub Actions, including pipeline triggers and CI/CD concepts.\nManage source code and collaborative development using GitHub.\nWork within an Agile/Scrum environment and manage delivery through JIRA.\nSupport secure Azure implementations using Microsoft Entra ID and Azure Key Vault.\nProvide technical guidance while remaining hands-on with engineering and troubleshooting activities.\n Qualifikationen\n Qualifications\nRequired\nMust-Have Requirements\n5-7+ years of experience in Data Engineering, Data Analytics, Data Platforms or a related technical environment.\nStrong hands-on experience with Microsoft Azure, Azure Databricks, Azure Data Factory, Azure Data Lake Storage, Microsoft Entra ID / Azure Active Directory, and Azure Key Vault.\nStrong programming and data manipulation skills using SQL and Python.\nProven experience in Power BI report development.\nExperience using GitHub for source control and collaborative development.\nUnderstanding of Azure DevOps Pipelines and/or GitHub Actions, including triggers and CI/CD concepts.\nGeneral understanding and practical experience working with APIs.\nExperience working within Agile/Scrum environments and using JIRA.\nProven ability to lead technical projects and coordinate delivery across multiple parties.\nStrong stakeholder management skills across business, technical, vendor and global teams.\nAbility to work independently within a flat structure and with minimal supervision.\nExperience\nExperience working in Agile/Scrum environments.\nExperience with Azure Data Platform technologies.\nExperience developing enterprise-grade ETL/ELT pipelines.\nExperience supporting data warehouse, data lake and analytics platforms.\nExperience working with source control tools such as GitHub or Azure Repos.\nExperience with Jira and Confluence.\nSpecific Knowledge / Skills\nStrong analytical and problem-solving skills.\nPassionate about improving data quality, platform reliability and scalability.\nStrong stakeholder management and communication skills.\nAbility to work independently while collaborating across multiple teams.\nProduct-oriented and results-driven mindset.\nKnowledge and Skills\nData Engineering\nStrong SQL and Python/PySpark development.\nExperience building and supporting ETL/ELT pipelines.\nData modelling experience including Star Schema, Snowflake Schema and Medallion Architecture.\nExperience with batch and streaming data processing.\nExperience developing data quality, validation and monitoring frameworks.\n\nCloud & Platform\nMicrosoft Azure\nAzure Databricks\nAzure Data Factory\nAzure Data Lake Storage (ADLS)\nAzure Synapse Analytics (nice to have)\nAzure Key Vault\nAzure DevOps Pipelines\nGitHub Actions\nDatabricks & Big Data\nApache Spark / PySpark\nDelta Lake\nDatabricks Workflows\nUnity Catalog (nice to have)\nHive Metastore (nice to have)\nVisualization & Reporting\nPower BI\nDAX\nData Analytics and Reporting\nDevOps & Engineering\nGitHub / Azure Repos\nCI/CD\nDocker\nTerraform (nice to have)\nDatabricks CLI / Azure CLI (nice to have)\nNice to Have\nFastAPI\nRedis\nNATS\nKusto Query Language (KQL)\nAzure Log Analytics\nPowerShell / Bash","description_format":"text","description_chars":5710,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Cafeteria","Flexible schedule"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Sports Organizations","Automotive Manufacturing","Exhibitions"],"lifecycle":[{"event":"open","at":"2026-10-27T12:04:24Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring 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