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Familiarity with data privacy standards, methodologies, and best practicesPractical hands-on experience with data technologies and Cloud Platform like Hadoop, Hive, Redshift, Big Query, Snowflake, Databricks, GCP and Azure.
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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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Design and deploy large-scale data applications using Cloud, Big Data, Azure Data Factory (ADF), Azure Data Bricks, Python, Spark, SQL and NoSQL solutions. NET; C#; HTML; REST APIs; CSS; JavaScript; jQuery; Angular; SharePoint; Python; Shell Scripts; SQL Server; Oracle; NoSQL DBs; Cloud Technologies such as Azure and AWS; Git; Lucid Chart; Postman; Jenkins; Azure DevOps; Kubernetes; and Docker.
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Familiarity with big data technologies, such as Amazon Redshift, Google BigQuery or Snowflake. Knowledge of machine learning algorithms and data analysis techniques for optimizing ad targeting and performance.
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Experience working with Big Data technologies: Spark, Databricks or other frameworks. The candidate should possess intellectual acumen, with an engineering mindset and an interest in developing enterprise scale solutions using industry recognized cloud platforms, databases, data integration/orchestration tools, and big data technologies.
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4+ years of experience with Big Data technologies including Spark/Databricks, Hadoop, and varying types of Azure Storage. 8+ years of data engineering or data analysis experience using core data tools as Azure Data Factory, SSIS, and Apache Airflow and use of languages such as SQL, Python, R, and Excel.
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We seek a Data Engineer who brings a robust skill set and extensive experience in cloud-based data engineering experience particularly within the realm of Azure and Databricks using Python, PySpark and cloud SQL. Critical thinking and problem-solving abilities are paramount, as you will navigate evolving and complex requirements and collaborate with stakeholders across diverse technical backgrounds.
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Experience working with big data distributed programming languages, and ecosystems such as Spark, Hadoop, MapReduce, Pig, Kafka. Experience with common data science tools such as Python, R, PyTorch, TensorFlow, Keras, NLTK, Spacy, or Neo4j, and a good understanding of modelling platforms such as Azure AutoML, SageMaker, DataBricks, DataRobot, and H2O.ai.
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Solid understanding of data engineering concepts, including data modeling, data processing pipelines, and big data technologies (e.g., Hadoop, Spark, Kafka). Experience working with relational and NoSQL databases, as well as cloud-based data storage solutions (e.g., AWS S3, Google Cloud Storage, Azure Blob Storage.
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Google Cloud Platform, ideally with Google Big Query, Cloud Composer and Cloud Data Fusion, Cloud spanner, Cloud SQL. The client is seeking a Sr. level Data Engineer, with experience in Google Big Query, GCP, ETL Pipeline, BI, Cloud Skills, Microsoft SQL with experience in both building and designing.
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Build and maintain data pipelines and ETL processes using tools such as DBT Labs and Databricks. Implement robust security and compliance measures in Azure, Snowflake, and Databricks to protect sensitive data and meet regulatory requirements.
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Knowledge of big data platforms like Snowflake, DBT, AWS Redshift, Postgres, MongoDB, and Hadoop. Strong experience in building ETL data pipelines and analysis using Python, SQL, and PySpark.
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Support vendor risk management and DPIA programs to ensure third parties comply with the Firm’s privacy and data protection requirements. This role requires Data Loss Prevention (DLP) program experience, including conducting investigations related to data loss, data exfiltration, or unauthorized access or use of data, or experience using eDiscovery solutions or similar technology.
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Good command of database technology and query languages (SQL) and non-relational DB and other Big Data technology, including efficient storage and serialization protocols (e.g. Parquet, Avro, Protocol Buffers.
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Should have in depth understanding on Data Warehousing, Master Data Management (MDM), Data Quality, Data Lineage, Data Modeling, Data Profiling and Data Policy and handled Data Governance programs.
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big data jobs Title: developer Company: Walt Disney in Dallas, TX
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