Data Engineer I - Data Engineering

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Job Description: Data Engineer I - Data Engineering

What You Will Be Doing

Primary Duties and Responsibilities:

• Work with business stakeholders to identify business problems, opportunities, and initiatives for which analytics models may provide insights that drive the development of solutions.
• Conceptualize, design, and develop analytics models to address complex business problems, discover insights, and identify opportunities using a hypothesis-driven approach.
• Translate data into information and insights with clear scenario analysis, business impact, and execution plans to drive impact.
• Collaborate with team members to include accurate and relevant data for machine learning models, identify potential proxy data sources, and design business analytics solutions considering future needs, infrastructure, and security requirements.
• Conduct data analysis and design and develop moderately complex analytic algorithms.
• Model and frame business scenarios that impact critical business processes and decisions.
• Collaborate with subject matter experts to select relevant information sources, translating business requirements into semantic access, conceptual, logical, and physical data models.
• Execute data profiling and preventative procedures to improve data quality; use technology to extract and analyze raw data.
• Identify opportunities and support the development of automated solutions to enhance enterprise data quality.
• Code, test, debug, and document complex programs, and enhance existing programs to ensure that data processing systems meet user requirements.
• Develop specifications for customer and user-specific reports, including network exclusions, special circumstances, and custom data elements.
• Identify complex areas to solve new technical problems and provide innovative technical solutions within data science and machine learning.

Responsibilities

• Design, develop, test, deploy, and maintain data processing systems.
• Build scalable data pipelines using Azure Data Factory to extract, transform, and load structured and unstructured data.
• Implement secure storage and access controls for sensitive data using Azure Key Vaults.
• Leverage Azure Databricks for advanced analytics tasks, including ETL jobs and machine learning workflows.
• Utilize Spark fundamentals to optimize the performance of big data processing tasks.
• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
• Ensure data quality by implementing appropriate validation checks and error-handling mechanisms.
• Work closely with DevOps teams to integrate data engineering processes into CI/CD pipelines.
• Monitor the performance of data pipelines and troubleshoot any issues that arise.
• Document technical specifications, processes, and best practices.

Requirements

• Bachelor's degree in Computer Science or a related field (or equivalent work experience).
• Proven experience as a Data Engineer or a similar role working on large-scale projects.
• Expertise in Azure services such as Data Factory, Key Vaults, and Databricks (Auto Loader, Unity Catalog, Workflows).
• Proficiency in Spark fundamentals for efficient big data processing.
• Solid knowledge of version control systems like Git/ADO for managing code base changes.
• Strong understanding of SQL for querying relational databases efficiently.
• Experience with Python programming language for scripting ETL processes and automating tasks.
• Familiarity with CI/CD concepts and practices in the context of data engineering workflows.
• Familiarity with legacy ETL tools such as SSIS and Informatica.
• Excellent problem-solving skills with attention to detail.

Preferred Qualifications

• Certification(s) in relevant technologies such as Azure or Databricks.
• Familiarity with other cloud platforms like AWS or GCP.
• Experience working with other ETL tools like SSIS, Informatica, or SAP BODS.

What Your Background