Senior Data Architect with Automation Engineering
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Position: Senior Data Architect with Automation Engineering
Location: Central PA
Duration: 6 Months Contract to Hire
Rate $ Open per Hour on W2
Job Summary:
We are seeking a Data Automation Engineer Unicorn to take on a pivotal role in designing, building, and automating data architectures, pipelines, and business processes. This unique position combines the skills of a data architect, data engineer, and process automation engineer to deliver end-to-end data solutions that drive business transformation. The ideal candidate will be proficient in Data Lakehouse like Data Bricks or Microsoft Fabric, Enterprise Reporting suites like Microsoft Power BI, Microsoft automation technologies, including Power Platform, SharePoint, and Azure, with expertise in scripting, data integration, process automation, and data governance. This role involves collaborating directly with business stakeholders to develop tailored solutions that streamline workflows, improve data quality, and deliver actionable insights.
Key Responsibilities:
End-to-End Data Architecture and Automation:
Design and implement both cloud-based and on-premises data architectures to support business needs, with a focus on scalability, performance, and security.
Build and maintain automated data pipelines and business processes, leveraging tools like Power Automate, Azure Data Factory, and other ETL/ELT platforms.
Create and implement data acquisition scripts, data flow designs, and custom integrations using a variety of tools (SQL, Python, PowerShell, etc.).
Data Pipeline and Workflow Development:
Develop and automate data ingestion, transformation, and delivery processes, ensuring data flows efficiently from multiple sources to end-user applications.
Automate business processes and repetitive tasks using Power Platform, SharePoint workflows, and other automation tools, improving operational efficiency.
Write scripts for data extraction, processing, and integration across cloud services like Azure, AWS, and on-premises databases.
Data Quality, Cleansing, and Testing:
Implement robust data cleansing strategies, ensuring that data entering systems is accurate, consistent, and ready for analysis.
Create and manage test data and testing scripts to validate automated workflows and data pipelines.
Perform ongoing data reviews and apply best practices for data governance, ensuring compliance with relevant regulations (GDPR, HIPAA, etc.).
Collaboration with Business SMEs and Stakeholders:
Engage directly with business subject matter experts (SMEs) to gather detailed requirements, ask probing questions, and ensure a deep understanding of business processes.
Translate business needs into technical specifications and automated solutions, aligning with organizational goals and optimizing processes for scalability.
Work in close coordination with data architects, data scientists, and developers to build integrated data systems and solutions.
Documentation and Process Standardization:
Document data architectures, data pipelines, scripts, and automation workflows to ensure transparency and scalability across the organization.
Provide training to business users and technical teams on new automated processes and tools, ensuring effective adoption and maintenance.
Continuously review, refine, and optimize automation workflows and data systems, improving performance and reliability.
Performance Optimization and Continuous Improvement:
Monitor and troubleshoot data pipelines, scripts, and automations, identifying bottlenecks and inefficiencies.
Use performance tuning techniques to optimize SQL queries, scripts, and data flows for speed and efficiency.
Stay up to date with the latest in data technologies and automation trends, continuously improving the organization's data infrastructure and capabilities.
Required Skills and Qualifications:
Education:
Bachelor s or Master s degree in Computer Science, Information Systems, Engineering, or a related field.
Experience:
7+ years of experience in data architecture, engineering, and process automation, with hands-on expertise in Microsoft technologies (Power Platform, Azure, SharePoint).
Proven experience in designing and implementing data architectures, both cloud-based (Azure, AWS) and on-premises, with strong knowledge of ETL/ELT processes.
Expertise in developing scripts (Python, PowerShell, SQL) for automation and data integration.
Extensive experience in data cleansing, validation, and testing, including creating and managing test data sets and automated test scripts.
Experience working directly with business stakeholders, gathering requirements, and delivering tailored data automation solutions.
Technical Skills:
Advanced knowledge of Microsoft Azure services (e.g., DataBricks, Data Factory, Fabric, Synapse Analytics, Data Lake) and Power Platform (Power Automate, Power Apps, Power BI).
Strong proficiency in SQL for database design, query optimization, and ETL development.
Expertise in Python, PowerShell, and other scripting languages for automation and data engineering tasks.
Familiarity with cloud-based solutions (Azure, AWS, Google Cloud Platform), data lakes, and data warehouse solutions.
Experience with Microsoft Graph APIs and integration with Microsoft 365 services for automation and workflow enhancement.
Proficiency with version control (e.g., Git) and CI/CD pipelines for automating development and deployment workflows.
Soft Skills:
Strong analytical and problem-solving skills, with a high attention to detail and a focus on delivering quality results.
Excellent communication and interpersonal skills, capable of translating complex technical concepts into business-friendly language.
Ability to manage multiple projects and priorities in a fast-paced, dynamic environment.
A proactive mindset, continuously seeking ways to improve processes, reduce manual effort, and increase efficiency.
Preferred Qualifications:
Certifications in Microsoft Azure, Power Platform, or related tools (e.g., Azure Solutions Architect, Azure Data Engineer).
Experience with big data technologies (e.g., Snowflake, DataBricks, Hadoop, Spark) and real-time data processing tools (e.g., Kafka, Azure Event Hubs).
Familiarity with Robotic Process Automation (RPA) tools like UiPath, Blue Prism, or Automation Anywhere.
Knowledge of process improvement methodologies (Lean, Six Sigma) and Agile practices.
Experience with containerization technologies (e.g., Docker, Kubernetes) and their use in data pipelines.
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