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.

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.

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 strong background in big data analytics, data engineering, and cloud computing, with a focus on building and optimizing data lakes on AWS. The Cloud Big Data Expert plays a crucial role in designing, implementing, and managing advanced data solutions using both AWS and Data Lakehouse platforms.

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.

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.

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.

Experience with the Big Data stack (HDFS, SPARK, MapReduce, Hadoop, Sqoop, Pig, Hive, Hbase, Flume, Kafka) as well as with the No-SQL (e.g. MongoDB, HBase, Cassandra) As a Data Engineering & Analytics practice lead you will be responsible for growth, business development and providing advisory and thought leadership on the provision of analytics environments leveraging Cloud based platforms, big data technologies, including integration with existing data and analytics platforms and tools.

Possess Data Warehousing principals and architecture patterns to help build reporting data marts in Oracle, Big Data platforms: Hadoop and Cloud data bases eg: Snowflake/Red Shift Experience and working knowledge in extracting data from traditional data warehouse, big data ecosystems and cloud data warehouses to produce critical data for business analyst executives and operational leaderships.

Certification in big data technologies or cloud data services ● Knowledge of Qlik/Qlik Sense, QVD/QlikView, and Qlik Production Application Standards (QPAS) is a significant plus Benefits: Our client provides a comprehensive benefits package designed to support your health, financial well-being, and professional development.

As a big data engineer at Booz Allen, you'll implement data engineering activities on some of the most mission-driven projects in the industry. We need an experienced data engineer like you to help our clients find answers in their big data to impact important missions-from fraud detection to cancer research to national intelligence.

Experience with at least 3 of the technologies/tools mentioned here: HAProxy, Kafka, Big Data/ Hadoop, Presto, Spark, Airflow, Pinot, Druid, Opensearch, Gcp, Data Proc. Experience scaling production systems running Big Data tools like Spark, Hadoop, Apache Druid, Looker.

As a data architect, you will focus on the big picture of an organization’s data strategy. We are open to proficiency in a variety of technologies: SQL, Bash, Python, Java, Presto, Spark, AWS, DataOps, DevSecOps, data streaming like Kafka, RabbitMQ, data stacks like Airflow, Databricks, dbt, and data stores like Cassandra, Aurora, ZooKeeper.

As a data engineer, you know that organizing big data can yield pivotal insights when it's gathered from disparate sources. Work with us to use big data for good. Experience with distributed data and computing tools, including Spark, Databricks, Hadoop, Hive, AWS EMR, or Kafka.

As a lead big data engineer at Booz Allen, you'll use your expertise to lead data engineering activities on some of the industry's most mission-driven projects. We need a big data professional like you to help our clients find answers in their data to impact important missions-from fraud detection to cancer research to national intelligence.

Experience solving Big Data batch and real-time data processing problems, with large-scale analytics and data processing engines such as Apache Spark and Databricks. Knowledge of Python data science tools, such as SciKit, Numpy, TensorFlow, Jupyter.