Data Engineer II

POSITION SUMMARY:

Responsible for independently designing, building, and maintaining scalable data pipelines and infrastructure to support company data-driven initiatives. Take ownership of complex data systems, implement best practices, and collaborate closely with cross- functional teams to ensure the availability, reliability, and performance of the organizations data platform.

• Design, implement, and optimize end-to-end data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data
• Develop robust ETL/ELT processes to integrate data from diverse sources into the data ecosystem
• Implement data validation and quality checks to ensure accuracy and consistency
• Build analytical tools that provide practical insights into key business performance indicators
• Conduct code reviews

• Design and maintain data models, schemas, and database structures to support analytical and operational use cases
• Optimize data storage and retrieval mechanisms for performance and scalability
• Evaluate and implement data storage solutions including relational databases, No
  
  SQL databases, data lakes, and cloud storage services
• Generate architecture recommendations and implement improvements

• Configure and manage data infrastructure components including databases, data warehouses, data lakes, and distributed computing frameworks
• Monitor system performance, troubleshoot issues, and implement optimizations
• Implement data security controls and access management policies
• Plan and execute system expansion to support company growth and analytic need

• Build and maintain integrations with internal and external data sources and APIs
• Implement RESTful APIs and web services for data access and consumption
• Ensure compatibility and interoperability between different systems and platforms
• Work with SaaS application APIs (Salesforce, Zuora, Zendesk, Marketo)

• Collaborate with internal and external data scientists, analysts, and stakeholders to understand requirements and deliver solutions
• Document technical designs, workflows, and best practices
• Provide technical guidance and support to team members
• Perform technical interviews and contribute to hiring decisions

• Bachelor’s degree in computer science, data engineering, information systems, or related field or equivalent experience; master’s degree preferred
• 5+ years of hands-on experience in data engineering or related roles
• Professional experience using Python, Java, or Scala for data processing
• Solid understanding of SQL and analytical data warehouses (Snowflake, Redshift)
• Hands-on experience implementing ETL/ELT best practices at scale
• Experience with data pipeline tools (Airflow, Luigi, Azkaban, dbt)
• Strong data modeling skills and familiarity with Kimball methodology
• Experience with big data technologies (Hadoop, Spark, Kafka, Hive)
• Proficiency with cloud platforms (AWS, Azure, or GCP) and their data services
• Experience with stream-processing systems preferred
• Knowledge of Data Lifecycle Management processes preferred
• Familiarity with Agile methodologies preferred
• Understanding of data governance and security best practices
• Relevant certifications (Google Professional Data Engineer, AWS Data Analytics, Cloudera CCP)
• Excellent communication skills
• Able to work independently and as part of a team
• Willing to share knowledge and experience with other members of the team
• Strong analytical and problem-solving skills
• Attention to detail and commitment to data quality
• Solid planning and organizational skills
• Proficiency with Microsoft Office Suite of programs

• Ability to effectively communicate at all levels within the organization through written and two-way verbal communication
• Able to read and write at a high school graduate level
• Able to sit or stand for extended periods of time
• Able to operate various office equipment (e.g., personal computer, telephone, fax machine, copier, etc.)
• Able to lift 10 to 20 pounds
• Able to work overtime and regular and/or extended (evenings, nights, and weekends) office hours to meet established deadlines
• Able to travel independently to support Company objectives and personal development