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Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark. Feature Engineering and Optimization: Develop and maintain ETL pipelines using orchestration tools such as Airflow and Jenkins; deploy scalable streaming and batch data pipelines to support petabyte scale datasets.
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Production experience with developing content recommendation algorithms at scale and familiar with metadata management, data lineage, and principles of data governance. Our team develops, implements, and maintains recommendation and personalization algorithms for Disney Streaming’s suite of streaming video apps, notably Disney+ and Hulu. As a member of this team you will collaborate across Engineering, Product, and Data teams to apply machine learning methods to meet strategic product personalization goals, explore innovative, cutting edge techniques that can be applied to recommendations, and constantly seek ways to optimize operational processes.
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Big Data Technologies : Experience with big data technologies and tools such as Apache Spark, Hadoop, Apache Cassandra, and distributed computing frameworks for handling large-scale datasets.
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Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Redshift, Big Query) Expanding, scaling, and standardizing the core foundational principles through consistent observability, lineage, data quality, logging, and alerting across all engineering teams in the Data organization is imperative to the creation of a single pane of glass.
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Big Data Platforms : Experience with Databricks for big data processing and analytics. Certifications : AWS Certified Solutions Architect or AWS Certified Big Data – Specialty.
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Empresa global de capital privado especializada en outsourcing de innovación, dedicada a la prestación de servicios de desarrollo y diseño de software, modernización de aplicaciones, RPA, machine learning y Big Data, entre otros.
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The Sr. Enterprise AI Strategy Advisor ( Sr. Project Engineer - Computer Engineering - Data Science/Big Data Mining and Artificial Intelligence ) will execute Space Systems Architect Division mission by leveraging the Aerospace program office and engineering technology group backplane to collaboratively develop and assist in execution of SSC's Enterprise AI Strategy and Implementation plans aligned to both the DoD and AI Strategy documents.
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Responsible for the documentation, implementation, startup, and technical support of Programmable Logic Controller(PLC) and Human Machine Interface (HMI) programming with an emphasis on SCAD (Supervisory Control and Data Acquisition.
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Análisis, diseño y desarrollo de modelos de datos corporativos (Data Lake / Data warehouse) en tecnología GCP (Bigquery / Dataflow/ Kubernetes / Composer)Requisitos:● Experiencia como líder técnico.
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Experience with ETL/ELT tools like ADF, Informatica, Talend, etc., and data warehousing technologies like Azure Synapse, Azure SQL, Amazon Redshift, Snowflake, Google Big Query, etc. Strong experience with big data tools (Databricks, Spark etc.
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At least 4 years of experience in data engineering working with Big Data Technologies: Apache Spark, Pyspark, Hadoop, and DataBricks with delta lake. Requires a minimum of a bachelor's or foreign equivalent degree in Management Information Systems, Computer Science and Engineering, or a related field plus 4 years of experience as a software developer, data engineer, or related occupation.
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Hands on experience with modern cloud data warehouse and engineering for one or more of the following cloud providers - GCP (Big Query, Vertex, Cognitive Services), Snowflake, Azure (Synapse, Dynamo, Cosmos, Azure ML, Power BI), AWS (Redshift, Sage maker), Tableau;Possessing a certification(s) in one of the following is a big plus – GCP/AWS/Azure/ data or ML engineering.
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YOUR SKILLS AND EXPERTISEBachelor’s degree in computer science, data science or a related field with five (5) or more years of working as a data engineer, ETL developer and/or data warehouse DBA.STANDOUT QUALIFICATIONS:Experience with Cloud-based data services and solutions (Azure Synapse / Data Lake, AWS RedShift, Snowflake, GCP Big Query)Experience partnering with Analytics and Data Science teams in building out production grade GenAI/ML solutions.
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In HADOOP , you'll be given an introduction to BIG DATA, APACHE HADOOP, HADOOP ECOSYSTEM, CLOUDERA QUICKSTART VM along with core concepts of the Hadoop framework including MapReduce, HIVE, PIG, SQOOP, FLUME, HBASE, OOZIE.
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Experience with big data tools and architectures, such as Cloudera Hadoop, HDFS, Hive, and Spark. THE ROLE:As a key member in the Advanced Data Analytics team, the Data Analyst will work with this and a cross-functional team to develop and execute the data analytics strategy and apply to Oshkosh Corporation products.
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big data jobs Title: representative Company: Vector Marketing in NC, Canada
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