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A high-growth Mobility & Smart Transportation tech company engineering an intelligent, algorithmic fleet management and optimization platform. Founded by seasoned industry veterans and backed by a leading global automotive fleet corporation following an acquisition, the company maintains complete operational autonomy and an agile startup culture. The platform leverages advanced predictive models and big data to automate demand forecasting, dynamic pricing, and vehicle dispatching for global car rental companies, car-sharing operators, and automotive OEMs. Located in central Tel Aviv (approx. 10-minute walk from the train station), operating on a hybrid work model. Role Description- Serving as a Senior Data Infrastructure & Pipeline Engineer, leading the design, implementation, and scaling of core enterprise data systems across batch and real-time streaming architectures. Architecting, developing, and maintaining high-throughput ETL / ELT Data Pipelines using Python, Apache Spark, and SQL. Designing dimensional data models, Data Marts, and analytical storage layers in modern Cloud Data Warehouses (Snowflake / GCP / AWS). Orchestrating robust data workflows and pipeline scheduling utilizing Apache Airflow / DBT. Deploying and scaling containerized data services within Docker and Kubernetes (K8s) environments under modern CI/CD practices. Collaborating cross-functionally with Machine Learning Engineers, Data Scientists, Product Managers, and Core Backend squads to power algorithmic mobility decision-engines. Requirements- 4+ years of hands-on experience as a Data Engineer or in Data Infrastructure Development – Mandatory Strong programming proficiency in Python for data processing and pipeline development – Mandatory Advanced, deep hands-on expertise in Complex SQL, Query Optimization, and Data Modeling – Mandatory Proven track record in building and scaling Large-Scale Data Pipelines (Batch & Streaming) – Mandatory Hands-on experience with big data processing frameworks (Apache Spark, PySpark, or Apache Flink) – Mandatory Practical experience with workflow orchestrators (Apache Airflow) and Cloud Platforms (AWS / GCP) – Mandatory Experience with real-time streaming (Apache Kafka) or modern data modeling tools (DBT, Snowflake) – Significant Advantage Background in Mobility, IoT Data Streams, FinTech, or Geospatial Analytics – Advantage
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.