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Mentor junior engineers in software and data engineering best practices. Build and deploy batch and streaming pipelines to collect and transform our rapidly growing Big Data set within our hybrid cloud architecture utilizing Kubernetes/EKS, Kafka/MSK, and Databricks/Spark.
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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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Five or more years’ experience with designing and maintaining data warehouses and/or data lakes with big data technologies such as Spark/Databricks, or distributed databases, like Redshift and Snowflake, and experience with housing, accessing, and transforming data in a variety of relational databases.
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Requirements: Requires a Bachelor’s degree (or foreign equivalent) in Computer Science, Computer Engineering, Software Engineering or related field and 6 years of progressively responsible, post-baccalaureate experience as a Software Engineer, Applications Development Senior Programmer Analyst, ETL Developer, or related position involving Ab Initio ETL standards in Data warehouse applications.
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Performs software engineering and development activities associated with supporting, maintaining, and enhancing software using an Agile DevSecOps model. The purpose of this effort is to advance the state of the art in Big Data, data analysis, Artificial Intelligence (AI), Machine Learning (ML), and advanced analytics to enhance the DoD’s and the IC’s information processes and technical architectures.
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6+ years of experience in data engineering working with big data systems that can process and transform data at scale. As a technical leader of our data engineering team, reporting to our Director of Business Intelligence, you'll play a pivotal role in defining the foundation crucial for various types of analysis.
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The candidates should have demonstrated knowledge and interest in Bioinformatics, Data Engineering and Software Development. Developer- Bioinformatics, Java/Scala, JavaScript, Data Engineering.
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Design and build production data engineering solutions to deliver our pipeline patterns using Google Cloud Platform (GCP) services: BigQuery, DataFlow (Apache Beam), Pub/Sub, BigTable, Data Fusion, DataProc, Cloud Composer (Apache Airflow), Cloud SQL, Compute Engine, Cloud Functions, and App Engine.
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Demonstrated expertise in big data technologies, including Apache Spark, Scala, Python, SQL, and TEZ. At least 8 years of deep data engineering experience focusing on Spark and SQL application development.
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We are currently seeking an experienced Machine Learning Engineer/Software Developer to join the Big Data and Advanced Analytics department. As part of the Data Analytics team, the Lead Data Scientist will work closely with the Data Engineering team and business functions to solve real-world oil and gas midstream problems using machine learning, data science algorithms and artificial intelligence.
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Experience using Autodesk Inventor software for 3D modeling, assembly design, and engineering documentation. Our capabilities range from C5ISR, AI and Big Data, cyber operations and synthetic training environments to fleet sustainment, environmental remediation and the largest family of unmanned underwater vehicles in every class.
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Must have six (6) years of experience with: Hands-on software development, data engineering, and systems architecture; Data Lake Infrastructure, Data Warehousing, and Data Analytics tools; Developing Enterprise Data Models; Data modeling, data warehousing, and building high-volume ETL/ELT pipelines; Building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets.
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Work with business users, data product owners, platform owners, enterprise architects, data management owners, and data engineering teams to ensure the data supply chain and the enterprise data products are built with high performance, high availability, and maintainability standards using current and emerging big data technologies.
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Skills: azure data factory (adf),azure data engineering,python,big data technologies,databricks,azure,pyspark,sql. The ideal candidate will be proficient in tools and technologies like Pyspark, Azure Data Factory (ADF), Databricks, big data technologies, SQL, and Python.
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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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big data software engineering jobs Title: stack developer
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