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Collect ADAS big data for all vehicle tuning/calibration activities to aid triage and issue resolution. Suggest software strategy updates as needed based on outcome from data collected during calibration development.
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Actively leading the technology domain that includes data architecture, data engineering (inclusive of big data supporting data science), data integration, data operations, and business strategy that advances ideas into transformational new capabilities.
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Expertise in advanced data science, machine learning, and artificial intelligence techniques, supported by a strong track record in programming languages such as Python, R, SQL, and proven software engineering methodologies.
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The Lead Big Data Developer, working independently, will develop, test, debug and document software components commensurate with their experience as well as direct development staff in support of a software engineering effort.
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Fluent in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. What you’ll be responsible for:As a member of the Data Engineering - Business ETL team, you own the data warehouse and data pipelines that are used for financial and regulatory reporting.
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77 West Wacker Dr (35012), United States of America, Chicago, Illinois Director, Software Engineering - Partnerships We are seeking a Director of Software Engineering who is passionate about growing and sustaining an innovative technology organization while fostering a culture of engineering and operational excellence.
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Minimum of 10 years of experience in backend software development, with a strong focus on data engineering and big data technologies. Proven experience building enterprise-grade software in a cloud-native environment (GCP or AWS) using cloud services such as GCS/S3, Dataflow/Glue, Data proc/EMR, Cloud Function/Lambda, Big Query/Athena, Big Table/Dynamo.
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Tops 3 Skills Needed Data Engineering 5 years Data Bricks 5 years Py Spark 5 years Years of Experience: 12 years Technology requirements: Proficiency in Apache Spark, including Spark Core, Spark SQL and Spark Streaming.
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Must have Master's degree or foreign equivalent in Computer Science, Computer Engineering, Information Technology, Electronic Engineering, or a related field and 2 years experience in the proffered position, or as a Developer, Software Engineer, Technology Analyst, Programmer Analyst, or related occupation.
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Security Engineering is an integral part of Trust & Safety and has a critical role to play in keeping customer data from bad actors. Represent the security engineering discipline throughout the organization, having a powerful voice to make us more data-driven.
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More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow.
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KEY QUALIFICATIONS: Python, SQL Data processing, ML experience Data Warehouse knowledge ETL pipeline knowledge Data Engineering Data Science Data Analytics, Data Mining PLEASE HAVE KNOWLEDGE OF ONE OR MORE OF THE FOLLOWING TECHNICAL SKILLS: Kubernetes, Tableau, PowerBi MongoDB Microsoft Cloud Services like Azure and AKS Snowflake SQL Server data platform Software development (including design, implementation, testing, and change management.
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Engineering Physicists are responsible for all aspects of laboratory, product, manufacturing & test automation, including hardware and software integration including Real-time and Windows OS, National Instruments, LabVIEW, FPGA, Rockwell, PLC, HMIs, SolidWorks & Python development, as well as pioneering the use of scientific tools and methods to creatively solve client problems.
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Proficient with statistical and data visualization software e.g. JMP, Minitab, SQL. BS, MS in materials science or engineering, mechanical engineering, powder metallurgy, nanotechnology, applied physics, chemical engineering, or related field.
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In-depth knowledge of big data technologies such as Hadoop, Spark, Kafka, and cloud platforms such as AWS, Azure, GCP, Snowflake, Databricks, etc. Preferred Qualifications:Professional certifications in cloud computing (e.g., AWS Certified Solutions Architect, Microsoft Certified Azure Solutions Architect, Azure Data Engineer, SnowPro Core) and/or big data technologies.
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