Senior Data Ops Developer

• Design, implement, and maintain cloud-based data pipelines that support the efficient ingestion, storage, processing, and analysis of large volumes of data.
• Partner with data engineers, analytics teams, and business stakeholders to understand requirements and translate them into scalable, reliable, and maintainable technical solutions.
• Build automated solutions supporting Quote-to-Cash, Quote-to-Fulfillment, Analytics, and other business processes.
• Evaluate and use appropriate Azure infrastructure and cloud services, considering scalability, performance, extensibility, cost, security, and operational support.
• Integrate data from multiple disparate sources while maintaining data quality, integrity, accuracy, and timeliness.
• Design and optimize data storage and processing solutions, including data lakes, data warehouses, data marts, Azure SQL, and Spark-based workflows.
• Perform all responsibilities in accordance with company policies, procedures, security requirements, and internal controls.

• 2–3+ years’ experience in data engineering, analytics engineering, Data Ops, business intelligence engineering, or a related technical field.
• Strong SQL skills and experience working with data pipelines, data platforms, data warehouses, data lakes, or similar data environments.
• Experience gathering requirements from business stakeholders and explaining technical concepts clearly to technical and nontechnical audiences.
• Strong analytical, strategic-thinking, and creative problem-solving skills, with curiosity to identify trends, investigate details, and improve processes.
• Excellent written and verbal communication skills, with the ability to synthesize significant amounts of information and tailor it to the intended audience.
• Ability to work independently, take ownership of assignments, and collaborate effectively as a positive and proactive team member.
• Bachelor’s degree in Computer Science, Information Systems, Data Science, Engineering, or a related field, or equivalent practical experience.

Demonstrates expertise in designing and implementing cloud-based data pipelines, with strong proficiency in SQL and experience in data storage solutions such as Azure SQL and data lakes. Capable of collaborating with stakeholders to translate business requirements into scalable technical solutions while ensuring data quality and integrity.

• Data Engineering
• SQL Skills
• Cloud Services (Azure)
• Data Pipeline Development
• Analytical Problem-Solving

• Data Pipeline Development
• SQL Skills
• Data Warehousing
• Data Lakes
• Data Processing Solutions
• Data Integration
• Data Quality Management
• Data Ops
• Business Intelligence Engineering
• Analytics Engineering

• Analytical Skills
• Strategic Thinking
• Creative Problem-Solving
• Written Communication
• Verbal Communication

• Cloud-Based Solutions
• Quote-to-Cash
• Quote-to-Fulfillment
• Data Quality
• Business Processes

• Azure SQL
• Spark
• Data Lakes
• Data Warehouses
• Data Marts