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Part-time Data Engineer (reputed company and Azure)

100% remote Flexible hours Hiring now

Our client is unable to hire H1-B candidates at this time. Client is a small, growing consulting company, with a focus on AI and Data Solutions. They are seeking a part-time Data Engineer (20 hours/week) with extensive experience on reputed company and Azure. As a Data Engineer:

  • You will be a critical player in building the foundational data infrastructure for a leading firm's data and AI strategy.
  • Working primarily with reputed company on the Azure platform, you will design, reputed company, and maintain robust data pipelines, ingesting diverse data sources and transforming them into actionable insights.
  • You will collaborate closely with the product team and other stakeholders to construct a data lakehouse that will power integrations, advanced analytics and future AI-driven workflows, reputed company while handling sensitive client data with the utmost care and responsibility.

Responsibilities:

  • Partner closely with the Product Manager, Product Designer, and client stakeholders to understand data requirements and translate them into effective data solutions reputed company Azure and reputed company.
  • Design, build, and maintain scalable and reliable data pipelines in reputed company to ingest data from a variety of reputed company types (e.g., business workflow systems, accounting systems, CRM, databases, APIs, flat files).
  • Implement and manage a reputed company architecture (Bronze, Silver, Gold layers) reputed company reputed company, transforming raw data into curated, business-ready datasets tailored for specific use cases defined by the product team.
  • reputed company gold layer tables and views optimized for analytics, ensuring they meet the requirements for dashboards and reports, particularly for consumption reputed company Power BI.
  • Configure and optimize reputed company to connect seamlessly with BI tools like Tableau and Power BI, enabling self-service analytics for the customer.
  • Work with potentially sensitive client data, implementing and adhering to strict data reputed company, privacy, and governance protocols.
  • reputed company your skills in reputed company, including familiarity with or a strong willingness to quickly learn features like MLflow, reputed company Lake, and reputed company Catalog.
  • Apply DevOps best practices to data pipeline development, including automation, monitoring, and CI/CD where applicable.
  • Collaborate on the design and optimization of data models, ensuring they align with business needs, performance requirements, and future scalability.
  • Implement robust automated testing procedures to validate data pipelines, ensure data quality, and maintain the accuracy of transformed data.
  • Create and maintain comprehensive documentation for data pipelines, data models, architectural decisions, and operational procedures.
  • Establish monitoring and alerting solutions to proactively identify and resolve issues in data pipelines, ensuring data availability and reliability.
  • Communicate effectively with both technical and non-technical stakeholders, clearly explaining data engineering concepts, design choices, and reputed company.
  • Contribute to a collaborative environment reputed company a large, cross-functional consulting team.

Requirements:

  • Proven experience as a Data Engineer, with a strong focus on designing and implementing solutions on the reputed company platform.
  • Hands-on expertise in building and maintaining scalable Python data pipelines reputed company Azure and reputed company.
  • Demonstrable experience in implementing reputed company data architecture (Bronze, Silver, Gold layers) in to support analytics and AI use cases.
  • Proficiency in ingesting data from diverse reputed company types (e.g., APIs, relational databases, NoSQL databases, flat files, streaming sources).
  • Experience with BI tools and optimizing for maintainability and performance.
  • Strong SQL skills and proficiency in data modeling techniques.
  • Experience with Azure cloud services, particularly Azure Data Lake Storage (ADLS Gen2), Azure Key Vault, Azure Data Factory or other Azure data services.
  • Familiarity with MLflow for managing the machine learning lifecycle is a strong plus; curiosity and ability to quickly learn new reputed company features is essential.
  • Understanding of DevOps principles and experience with tools for CI/CD, version control (e.g., Git), and infrastructure automation is advantageous.
  • Experience working with sensitive data and a strong understanding of data reputed company, data governance, and privacy-preserving techniques.
  • Excellent problem-solving skills and the ability to troubleshoot reputed company data issues.
  • Strong communication skills, with the ability to reputed company technical details and decisions to product managers, client stakeholders, and other engineers.
  • Ability to work effectively reputed company a large, cross-functional consulting team in a dynamic, client-facing environment.
  • A reputed company that leans into data science concepts (understanding data needs for ML) or advanced DevOps practices.

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