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The Lead Data Engineer is responsible for orchestrating, deploying, maintaining and scaling cloud infrastructure targeting big data and platform data management (e.g., data warehouses, data lakes) including data access APIs. Prepares and manipulates data using Hadoop or equivalent.
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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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Job Title: Data Engineer/ Data ArchitectLocation: Corvallis, OR – 5 Days Onsite Role Job Description: At least 8 to 10+ years’ experience in data engineering , AI and ML and Aws/Azure Architect, Design and implement distributed data processing pipelines using Spark, Python, SQL and other tools and languages prevalent in the Big Data/Lakehouse ecosystem.
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Experience in developing partner led sales in collaboration with data platform and tool vendorsIn-depth knowledge of big data technologies such as Hadoop, Spark, Kafka, and cloud platforms such as AWS, Azure, GCP, Snowflake, Databricks, etc.
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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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Our client is currently seeking an experienced Data Engineer – Big Data individual for their Midtown office in Atlanta, GA. The successful candidate must have Big Data engineering experience and must demonstrate an affinity for working with others to create successful solutions.
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The big data architect will support the development of autonomous driving software solutions by playing the role of subject matter expert for the big data systems, underlying data and data products.
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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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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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Utilize Databricks for big data processing and streaming analytics. Experience with big data technologies such as Apache Hadoop, Spark, Kafka, and others. The ideal candidate will have a robust background in big data analytics, data engineering, and cloud computing, with a particular focus on building and optimizing data lakes on AWS. This role is crucial for designing, implementing, and managing advanced data solutions using AWS and Data Lakehouse platforms.
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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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Extensive experience with Cloud Data Warehouses such as Snowflake, Big Query, RedShift , including architecture, performance tuning, and security. Your team will manage the SDP data infrastructure, Terraform Cloud, Snowflake RBAC, and cost management for Snowflake and AWS. In addition to this, your team will also be tasked with developing Data Governance capabilities, specifically focusing on "Data Retention" and "Permission to Share.
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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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Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. Internal knowledge of open source or related big data technologies. As a member of the Data Engineering Web3 team, you own the ETL/ELT pipelines and data warehouse that are used to analyze trends and activity in our Web3 product offerings.
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big data jobs Title: entry level Company: Vector Marketing in DE, Germany
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