Senior Data Engineer at A-Line Staffing Solutions
Troy, MI 48085
About the Job
We Are actively building out an AI team. We are looking for people with a proven track record, who are willing to experiment with new ideas, invest time in them, fail-fast, and move on if they don't work out. We want team members who have shown a consistent interest in continuous learning, especially in Cloud Technologies, who are aware of, and follow the latest and best generative AI technologies and trends, can learn by themselves, are self-motivated and value self-directed initiative with technology and AI exploration. Summary As a Data Engineer, you will focus on creating a Unified Data Platform. You will design, develop, and maintain data pipelines, data lakes, and data platforms that support the analytics and business intelligence needs of our clients. You will work with cutting-edge technologies and tools, such as Spark, Kafka, AWS, Azure, and Kubernetes, to handle large-scale and complex data challenges. You will also collaborate with full stack developers, data scientists, analysts, and stakeholders to ensure data quality, reliability, and usability. You must be comfortable working with huge datasets.
NO C2C
Main Responsibilities
• Build automated pipelines to extract and process data from a variety of legacy platforms (predominantly SQL Server), e.g., in stored procedures, Glue processing, etc.
• Implement data-related business logic on modern data platforms, such as AWS Glue, Databricks, and Azure using best practices and industry standards.
• Create vector databases, data marts and the data models to support them
• Optimize and monitor the performance, reliability, and security of data systems and processes.
• Integrate and transform data from (or to) various sources and formats, such as structured, unstructured, streaming, and batch.
• Develop and maintain data quality checks, tests, and documentation.
• Support data analysis, reporting, and visualization using tools such as SQL, Python, Tableau and Quicksight
• Research and evaluate new data technologies and trends to improve data solutions and existing capabilities.