1. Data Engineer jobs in United States, January 2023

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Job Overview 

Job Description

You will work closely with process owners, product owners, and business users. You’ll collaborate in a hybrid environment with in-house, on-premise data sources and cloud and remote systems.

Responsibilities of Data Engineer

• Active contributor to code improvement in projects and services.
• Administer and scale data pipelines from internal and external data sources to manage new product launches and monitor data quality beyond data products.
• Develop and own the automation and monitoring infrastructure that captures metrics and operational KPIs for data pipeline standards and performance.
• Answerable for applying best practices around systems structure, security, performance, and data management.
• Empower the business by developing value through the increased adoption of data, data science, and business intelligence landscape.
• Work with internal clients (data science and product teams) to monitor POC discussions.
• Grow and optimize procedures to “productionalize” data science models.
• Define and administer SLAs for data products and processes running in production.
• Data scientists did Support large-scale experimentation was done by data scientists.
• Prototype new accesses and build solutions at scale research in state-of-the-art methodologies.

Qualifications of Data Engineer

• 2+ years of overall technology proficiency that adds at least 2+ years of first-hand software development, data engineering, and systems architecture.
• 2+ years of proficiency in SQL optimization and performance tuning and development proficiency in programming languages like Python, PySpark, Scala, etc.).
• 1+ years in cloud data engineering proficiency in Azure Certification is a plus.
• Proficiency with data modeling, data warehousing, and creating high-volume ETL/ELT pipelines.
• Proficiency with data profiling and data quality equipment like Apache Griffin, Deeqa, and Great Expectations.
• Proficiency in creating/operating highly available, deployed systems of data extraction, ingestion, and processing of large data sets.
• Proficiency with running and scaling applications on the cloud framework and containerized services like Kubernetes.
• Proficiency with version control systems like GitHub and categorization & CI instruments.
• Proficiency with Statistical/ML techniques is a plus.
• A plus proficiency in generating solutions in the retail or supply chain space.
• Knowledge of metadata management, data lineage, and glossaries is a plus.
• Working administration of agile development, including DevOps and DataOps concepts.
•  Identification Of business intelligence equipment (such as PowerBI).

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Education of Data Engineer

• BA/BS in Math, Computer Science, Physics, or other technical sectors.
• Master’s degree in Supply Chain/ Data Engineering
• Skills, Abilities, Knowledge

• Strong communication skills, both verbal and written, along with the potential to influence and significant confidence in communications with senior-level management.
• Authentic track record of leading and mentoring data teams.
• The high degree of organization and potential to manage multiple competing projects and priorities simultaneously.
• A positive and sustainable attitude enables adjusting to different requirements in an ever-changing environment.
• Excellent leadership, organizational and interpersonal skills; comfortable administering trade-offs.
• Potential to lead others without direct authority in a matrixed environment.

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