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Strong proficiency in data pipeline and ETL design, with hands-on experience in tools like Apache Airflow, Apache NiFi, or similar. Familiarity with modern cloud platforms (e.g., AWS, GCP, Azure) and their data engineering services.
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As a Sr Data Engineer you will create production data pipelines for our advanced analytics and data science teams - as well as collaborate with other technical personnel on internal & external data sources and infrastructure needs.
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Big Data Ecosystem | 2+ years of hands-on, professional experience with tools and platforms like Spark Streaming, EMR, Kafka. Proficiency in at least one programming language commonly used within Data Engineering, such as Python, Scala, or Java.
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Must be proficient and have hands-on working experience with Python, SQL, Javascript and various ETL/DW and data engineering tools. Work alongside the data science team to create and iterate concept prototypes with a focus on progress towards value over perfection.
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5+ years of hands-on data engineering experience with a strong understanding of healthcare data standards (e.g., HL7, FHIR), regulatory requirements (e.g., HIPAA) and experience working with electronic health records (EHR, EMR) data.
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Stay ahead of the curve: Stay up-to-date on the latest data engineering trends and technologies and champion their adoption to continuously improve our data infrastructure.
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5+ years of hands-on experience with a Mark Logic framework(required). Job Title: Sr. Data Engineer. Bachelor's degreein Computer Science, Computer Information Systems, Engineering, Statistics or closely related field (willing to accept foreign education equivalent) (required.
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Solid understanding of data warehousing concepts and hands-on experience with relational databases (e.g., PostgreSQL, MySQL) and columnar databases (e.g., Redshift, BigQuery, HBase, ClickHouse.
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Hands on experience working with data governance, data quality solutions. Expected ability to communicate and collaborate on data engineering tasks with internal and external teams.
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3+ years of hands-on distributed computing development experience using PySpark, Spark SQL, and Databricks. 5+ years of data engineering experience. As a Data Engineer, you will be collaborating to build a robust and highly performant data platform using cutting-edge technologies.
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Hands-on experience and knowledge of data lake technologies (Databricks, Snowflake, etc),data storage formats (Parquet, Avro etc.) Based on the project, this might involve cross-functional work with the Data Science, Analytics, and other Engineering and Business teams to design cohesive data models, database schemas and data storage solutions, consumption strategies and patterns.
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Strong hands-on experience with Apache Spark. Advanced proficiency in Python and SQL for data engineering. Strategy Creation: Collaborate with cross-functional teams to define the data engineering strategy aligned to business objectives, including data modeling that unifies data assets across a range of source systems used to manage the operations of our partnering hospitals.
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Knowledge or hands-on experience with streaming platforms and real-time data pipeline systems such as Apache Kafka, Azure Event Hubs, and similar platforms. Minimum of 10 years hands-on experience with Python and related data libraries (e.g. Pandas, Data Frames) Practical expertise in ETL/ELT technologies and methodologies.
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They are looking for a hands-on technical lead who can help drive this modernization from data architecture & design along with data engineering and technical leadership perspective.
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Hands-on experience building batch or streaming production data pipelines, ideally using one or more distributed processing frameworks such as Spark, Flink or Hive/Hadoop. Ads Data Engineering team sits at the core of building a data ecosystem that will power Netflix' understanding and decision making about what impact ads have on our business.
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hands on data engineering jobs Title: data engineer in Scranton, PA
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