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5+ years in designing, solutioning the Databricks, Snowflake, PySpark and Big data tools including DataOps, Data engineering, Data Integration, Data Orchestration and Data Marketplace.
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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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Alteryx, Banking, Business, Critical Thinking, Data Acquisition, Data Analysis, Data Management, Data Operations, Data Quality, Decision Making, Financial Products, Leadership, Management Reporting, Microsoft Power BI, People Management.
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Develop and optimize big data processing using Spark and PySpark within the Databricks environment. Design, build, and maintain scalable and reliable data pipelines using Infrastructure as Code (IaC) principles and Databricks along with Datadog.
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Good knowledge and Proven practical experience in migrating relational data base from on-prem to cloud OR to build cloud-based data lake using either Big Data / Azure Synapse / Databricks / Snowflake.
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Develop data, analytic, and data science models using Python, PySpark, Large Language Models (LLM) algorithms, and working with other big data tools such as AutoML, BigQuery(BQ), BQML, DataPrep and Jupyter Notebook.
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Our team leverages cutting-edge open-source technologies such as Apache Spark, Flink, Kafka, Airflow, Delta Lake, and Iceberg to build and maintain a scalable, high-quality data ingestion framework.
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You will construct semantic layers for Looker, MicroStrategy, Tableau, and In-House Tools on top of our big data warehouse, making sure the data is represented to analysts in an accurate, consistent, and performant way.
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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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The Senior Data Scientist is a member of the Data Science Center, which supports Cornerstone's litigation teams with data wrangling and advanced analytics programming in an environment with multiple simultaneous big data projects.
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Our transportation client is looking for a Big Data Engineer - Spark/Databricks to join their team. Experience with real-time data processing and streaming techniques using Spark structured streaming and Kafka.
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Driving Results: Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Python and/or Node.js, SQL (using dbt for transformation), commercial SaaS and OSS offerings, and AWS ‘big data’ technologies.
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Work on big data / machine learning / data science applied to important problems in biomedicine, supported by ample computational resources. This role is a great opportunity for gaining research skills in undertaking intricate computational projects that combine big data, high-performance computing, and algorithms.
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6 years of experience must include: Ab initio, Informatica, Data Stage; Teradata, IBM DB2, Cognos, Oracle PL SQL; Autosys, Control-M, Erwin, XML, HTML, CSS, Unix Shell Scripts; Data Analysis, Data Processing, Code Optimization, Performance tuning; Automating Business Process and Models; Microsoft Visio, Web Services, Crystal Reports; and HP Quality Center, ALM, VSS, EME, XSD. At least 3 years must include: Hadoop, HDFS, Big Data, Hive, Spark.
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Self-driven, challenge-loving, detail oriented, teamwork spirit, excellent communication skills, ability to multitask and manage expectationsNice to have:Experience in any of: machine learning, analytics, data mining, or data mart and warehouseExperience with Deep Learning platforms (Tensorflow/Keras/Spark MLlib) and SQL/Unix/ShellExperience with machine learning algorithms, NLP, and/or statistical methods a big plusYahoo is proud to be an equal opportunity workplace.
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big data quality jobs Company: Accenture in WA, Massachusetts
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