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Experience with data engineering concepts and challenges including data warehouse solutions, ETL, and distributed systems, as well as familiarity with and experience manipulating data in various formats, such as: avro, neo4j, json, cef, csv, w3c, pandas.
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Minimum of 5 years of hands-on skills in Python, Apache Spark, Hive, Cassandra, Snowflake, Elastic, Lucene, DataBricks, Hadoop, Redshift, Scala, Java, or other relevant technologies in data engineering.
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An understanding of data engineering and a knowledge of media data as the position will help with the advancement of our current warehouse solutions (built on the Datorama and Snowflake technology stacks), classifying real-time data for our clients and ensuring that the data has flowed through our warehouse solutions correctly for downstream user ingestion.
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We pursue a multi-disciplinary approach integrating data across biological scales in the brain, including molecular Chromosome-Conformation-Capture sequencing technologies, single-cell imaging, optogenetics, genome engineering, induced pluripotent stem cell differentiation to neurons/organoids, and in vitro and in vivo electrophysiological measurements.
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Hands-on expertise with data analytics, CRM, and visualization tools and platforms such as Python, R, SQL, Tableau, Power BI, HubSpot, Google Data Studio, and Google Analytics. This role reports into the Head of Technology and has direct management oversight of data engineering, data architecture, data operations, data science, data analytics, and data governance teams that design, build, and operate technology architecture, solutions, and software to capture, manage, store, and utilize structured and unstructured data from internal and external sources.
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Required Skills & Experience Proven experience in ETL data engineering with significant expertise using Python (PySpark) to perform data extraction, transformation, and loading from REST APIs, SQL database tables, and CSV files.
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With mentoring from the Principal Investigator, oversee and develop algorithms for analyzing ensemble genomics data, single cell genomics data, single cell merFISH and sequential oligopaints imaging data, as well as novel molecular connectomics data.
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3 years of experience with Esri ArcGIS desktop and enterprise products, knowledge of GIS data types, GPS collection, relational database management systems (RDBMS), spatial analysis, and cartography.
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Experience with programming languages (SQL, R, Python), front end design languages (HTML, CSS, JavaScript), developer packages such as Jupyter Notebooks. Process collected data using LiDAR Survey post-processing software, CAD software, and GIS software in preparation for import into Maximo and Geodatabase.
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Leading and managing a set of engineering-driven initiatives from ideation through delivery to production of high impact digital transformation and platform modernization initiatives utilizing data engineering and AI/ML technologies, while optimizing Agile practices and methodologies to enhance speed, flexibility, and delivery efficiencyImplement robust data ingestion, processing, and distribution pipelines to ensure timely and accurate data availability across the organization.
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Utilize programming languages like Java, Python, SQL, Node, Go, and Scala, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, Application Architecture like microservices, API, and realtime streaming, ETL and Data Engineering technologies like PySpark, Glue, Snowflake, and a variety of AWS tools and services.
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Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake. New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Mgr, Data Engineering.
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Proficiency in programming languages such as Python, Java, or Scala for data engineering and software development. Strong problem-solving skills and the ability to troubleshoot complex data engineering issues.
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5+ years of experience with Python and data engineering. We are looking for a highly-skilled remote data engineer that has experience with scripting in Python to pull in and normalize data from multiple varying APIs. Candidates should have experience with Python scripting, working with databases, working within the AWS cloud data tools, and working with standard developer tools.
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We use the most popular tools in the Python data science ecosystem and embrace innovation. Our core offerings – Bidder-as-a-Service (BaaS) and the Beeswax DSP – provide clients with agility, custom optimizations, and extensible APIs. We are looking for a Machine Learning Engineering with an in-depth working knowledge of the latest in Machine Learning/Data Science technologies and cloud platforms to join our Optimization team, which have three defining pillars: machine learning, software engineering, and machine learning operations (MLOps.
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