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Understanding of programming languages commonly used in data engineering and analytics (e.g., Python, R, Java, Scala) 5 – 7 years’ experience within positions with data management, database design, and data warehousing, with hands-on experience with modern data technologies and platforms (e.g., Python, SAS, SQL, NoSQL, Hadoop, Spark, AWS, Azure.
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6 years An equivalent of 6 years experience with big data, database query and analysis languages (e.g. Python, SQL, Snowflake SQL, R, Scala, SAS, Azure DataBricks) and data visualization tools (e.g. Power BI, Tableau) required.
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As part of the Data Engineering team, the Lead Python Data Engineer will work closely with Business domain experts and Data Scientists to solve real-world oil and gas midstream problems using advanced analytics, machine learning, and artificial intelligence.
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Our people extend into all industries we conduct work with our clients in the areas of; data science, data engineering, data strategy, intelligent process automation, data ecosystems, intelligent industry/IoT, enterprise management, customer-first marketing, and data partnerships/disruptors (such as SAP, Microsoft, Google, AWS, Snowflake, Oracle, Adobe, etc.
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Strong data science and data engineering background both with open source and cloud distributed machines learning and AI tools especially Azure Cognitive Services, Azure Machine Learning and AWS Sagemaker and Bedrocks.
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This role requires a strong background in backend development, data engineering, and experience with advanced data processing and machine learning techniques. We are seeking a highly skilled and experienced Senior Python Developer / Data Engineer to join our team.
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Ideally the candidate will be experienced with or have exposure to these tools and technologies: SQL, Snowflake, Data Modeling, Azure, SQL Server/AzureSQL, JSON, XML, Streamsets, Python, SSIS, PowerBI, API development, Java.
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Experience with common Python Data Engineering packages including Pandas, Numpy, Pyarrow, Pytest, Scikit-Learn, and Boto3. We are currently seeking an experienced Python Data Engineer to join the Big Data and Advanced Analytics department.
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This individual will provide analytical and technical leadership to the team to advance the data engineering practice within the organization. Work directly with Business domain experts and Data Scientists to develop high quality, reliable, scalable, machine learning systems.
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Automate manual data collection and processing tasks to improve efficiency. Design and implement frameworks and tools to streamline the machine learning process. Leverage software architecture and design patterns to develop fault tolerant microservices.
$91.24 - $109.48 an hourFull-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Mentor junior engineers and contribute to the growth of the data engineering team. in data engineering, with a focus on building and maintaining data pipelines. Experience with cloud-based data platforms (e.g., AWS S3, Redshift, Google BigQuery.
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Knowledge of Statistics, SAS, Python, Computer Vision, data visualization tools. entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Machine Learning engineers.
$75,000 - $155,000 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Analyst, Senior Data Engineering - 000EG2 Description Enterprise Products Partners L.P. is one of the largest publicly traded partnerships and a leading North American provider of midstream energy services to producers and consumers of natural gas, NGLs, crude oil, refined products and petrochemicals.
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The Senior Data Scientist will support the development of new analytics and data solutions through statistical modeling, feature engineering, machine learning and interpretation, and will lead projects with other Data Scientists and Economists in the broader Data & Analytics group.
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Job Title: Python Data Engineer. The candidate will have at least 7 years of programming experience in Python and expertise in developing and maintaining data pipelines. Additionally, the candidate should have experience with software engineering practices such as Design Principles and Patterns, Unit Testing, Refactoring, CI/CD, and version control.
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