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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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This person will assist in driving technology innovation for engineering projects and work on architecture of AWS, Data Lake (Databricks/Elastic) and Kubernetes. Produce progress reports on key infrastructures - Databricks, Elastic and Data Pipelines.
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Master's degree in a technical field (e.g. computer science, math, engineering Understanding of big data and real time streaming analytics processing architecture and ecosystems Experience with data analysis and data visualization tools Software development experience in relevant programming languages (i.e. Java, Python, Scala, Node.js) Relevant technology or platform certification (AWS, Microsoft, etc.
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Be the company's expert on data administration and master data management. Bring a system-oriented and software engineering mindset to the Data Engineering practice.
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Proactively drive innovation in big data and the execution of our data engineering and data warehouse frameworks and services. Our centralized Data organization (Analytics, Data Science, and Data Engineering) is a specialized, cross-functional group that collaborates with a variety of departments to drive decisions and provide direction for future growth at Brightcove.
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Ability to use a variety of relational, NoSQL, Postgres, and/or MPP databases (ideally Snowflake on AWS) and leading data modeling, schema design, and data storage best practices. Reporting to the Engineering Manager, you will be solving complex data challenges while designing and implementing data processing and transformation at a scale that powers state-of-the-art interactive product experiences.
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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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Documents all activities and may train and mentor others on how to support data engineering processes. Minimum of 4 years of experience in data engineering and software development.
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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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You'll be working directly with our data scientists, data engineers, Engineering team, and CTO on building pipelines and ad optimization models. #1 DSP on G2 and leader in a number of categories including Cross-Channel Advertising.
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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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As a Staff Software Engineer, you will be a technical leader, responsible for designing and driving software, tools, and a data architecture focused on enabling self-service adoption at scale.
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You will be operating with a high level of autonomy, collaborating directly with product, business partners, and peer engineering teams to align on data and reporting requirements.
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You will partner closely with collaborators on the data, product, engineering, design, and other teams, to create and optimize one-of-a-kind, data-driven products that will make it easier for low-income Americans to participate in government-funded assistance, stipend, and incentive programs.
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on engineering jobs Title: data engineer in Scranton, PA
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