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This role will provide expertise to support the development of a Big Data / Data Lake system architecture that supports enterprise data operations for the District of Columbia government, including the Internet of Things (IoT) / Smart City projects, enterprise data warehouse, the open data portal, and data science applications.
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3+ years experience with Big Data technologies, such asApache Hadoop, Hive or Spark, Databricks and/or Snowflake. The ideal candidate will lead the architecture and implementation of on-premises and cloud big data solutions as part of enterprise data modernization.
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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 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.
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Big Data Technologies: Distributed Computing: Tools like Apache Spark, Hadoop. Big Data Storage: Technologies such as HDFS, Apache Cassandra, or cloud storage solutions. Software Engineering & DevOps: Version Control: Familiarity with tools like Git. Continuous Integration/Continuous Deployment: Knowledge of pipelines and tools like Jenkins, Travis CI. Containerization: Familiarity with Docker, Kubernetes, etc., for scalable deployment of data science applications.
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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.
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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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Design, develop, and implement data architecture solutions using SQL Server, Microsoft Azure, Snowflake, and Databricks. The ideal candidate will have extensive experience in designing and implementing data solutions, with proficiency in SQL Server, Microsoft Azure, Snowflake, Databricks, and other relevant technologies.
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At Cognizant Digital Engineering, a small cross functional team comprised of a Product Manager, an Architect, Full-Stack Developers, UI/UX designers and Big Data analysts builds higher quality software faster siloed individuals working independently.
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Software Engineering/Data Engineering: data ingestion, streaming technologies - such as Spark Streaming and Kafka, performance tuning, troubleshooting, and debugging Spark or other big data solutions.
$150ExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Work on small projects analyzing a variety of big data covering national security, cyber security, business intelligence, online social media, human behavior and more. Previous experience performing research in data analytics or big data.
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Working knowledge of data visualization tools such as Qlik and Tableau. Support Federal government clients in a broad array of data science efforts. Lead a team of 2-3 data analysts / data scientists.
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Programming:Languages: Familiarity or proficiency in languages commonly used in data science, like Python, R, or Scala. Transform your career to the next level with GDIT as a Solutions Architect where you can elevate your skills in Data Science, Machine Learning, or leading AI techniques and technology expertise into solutions in support of our Government customers.
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Prior experience in Cybersecurity Operational Risk Management, supporting CISO in deployment and sustainment of cybersecurity capabilities, and previous big four experience preferred. Develop effective and measurable metrics (KRI, KPI and KCI) to analyze data and proactively identify trends or new/emerging risks.
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Experience with big data analytics, machine learning, artificial intelligence, or anomaly detection. Experience with DevSecOps, CI/CD, IaC and CaC, IT Infrastructure Library, and IT Service Management.
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Advance experience with developing Data Pipeline, ETL/ELT, utilizing tooling of Big Data Platform, Datalake, Synapse, Airflow, AirByte, Snowflake. Experience with Data Ingestion/ streaming tooling such as ADF (Azure Data Factory), Kafka, Five Tran, Spark, or similar technologies.
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big data jobs Title: developer Company: Simventions Inc Glassdoor in Mclean, VA
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