Senior Data Engineer

Ascendum System Private Limited; Cincinnati (OH); On-site; USD 135,000 - 185,000; Full time

Job summary

Ascendum System Private Limited is seeking a Data Engineer to design, develop, and support enterprise-scale data platforms. This role will lead migration from Netezza to Databricks, building scalable data pipelines and modern analytics capabilities for customer-facing retail operations.

The ideal candidate has 7+ years of data engineering experience, deep Databricks and PySpark skills, and strong SQL/data modeling expertise.

Qualifications

• Bachelor's degree in a related field.
• 7+ years of Data Engineering experience in enterprise environments.
• Strong hands-on experience with Databricks (required).
• Advanced proficiency in PySpark development.
• Experience developing both batch and streaming data pipelines.
• Strong SQL and data modeling expertise.
• Experience implementing data quality frameworks, validation processes, and reconciliation strategies.
• Experience building and maintaining automated testing and integration suites.
• Experience creating and supporting CI/CD pipelines for data platforms.
• Strong understanding of cloud-based data architectures and modern analytics platforms.
• Excellent communication and collaboration skills.

Responsibilities

• Provide migration support from Netezza to Databricks.
• Design, develop, and optimize scalable data pipelines with PySpark.
• Build batch and streaming ingestion frameworks for enterprise data.
• Implement data transformation strategies for modernization.
• Develop and maintain Databricks Lakehouse solutions with Medallion patterns.

Skills

Databricks

PySpark

Data migration

Test automation

CI/CD

Data quality

Medallion architecture

Streaming & batch processing

SQL

Data modeling

Netezza migrations

Education

Bachelor's degree in Computer Science, Information Systems, Engineering, or related field

Job description

• W2 candidates only, we cannot consider C2C or 1099 for this opportunity.
• Candidates should be eligible to work for any employer in the United States without needing Visa sponsorship

Data Engineer (Databricks)

Position Summary

We are seeking a highly skilled Data Engineer with 7+ years of experience designing, developing, and supporting enterprise-scale data platforms. This role will support a strategic initiative to migrate a legacy Netezza environment to Databricks, enabling next-generation analytics and data-driven decision making across customer-facing retail operations.

Key Responsibilities

• Provide support to the migration of legacy data assets from Netezza to Databricks.
• Design, develop, and optimize scalable data pipelines using PySpark.
• Build and support batch and streaming ingestion frameworks for enterprise data processing.
• Implement data transformation and conversion strategies to support platform modernization initiatives.
• Develop and maintain data solutions utilizing Databricks Lakehouse architecture and Medallion design patterns.

Establish And Enforce Engineering Best Practices, Including

• Coding standards
• CI/CD pipelines
• Automated testing frameworks
• Data quality validation processes
• Monitoring and operational support procedures
• Collaborate with business stakeholders, architects, analysts, and engineering teams to deliver high-quality solutions.
• Perform code reviews and mentor junior team members on data engineering best practices.
• Troubleshoot and resolve performance, scalability, and data integrity issues.
• Drive continuous improvement initiatives across the data engineering ecosystem.
• Support integration testing, regression testing, and production deployment activities.

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.
• 7+ years of Data Engineering experience in enterprise environments.
• Strong hands-on experience with Databricks (required).
• Advanced proficiency in PySpark development.
• Experience developing both batch and streaming data pipelines.
• Strong SQL and data modeling expertise.
• Experience implementing data quality frameworks, validation processes, and reconciliation strategies.
• Experience building and maintaining automated testing and integration suites.
• Experience creating and supporting CI/CD pipelines for data platforms.
• Strong understanding of cloud-based data architectures and modern analytics platforms.
• Excellent communication and collaboration skills.

Preferred Qualifications

• Experience with Netezza migrations or legacy Netezza environments.
• Experience with Delta Lake, Unity Catalog, and Databricks Workflows.
• Experience working with large-scale retail, customer, or omnichannel data platforms.
• Familiarity with Azure cloud services and modern data integration patterns.
• Experience with infrastructure-as-code and DevOps methodologies.
• Knowledge of data governance, lineage, and metadata management solutions.

Top Priority Skills: Databricks, PySpark, Data Migration, Test Automation, CI/CD, Data Quality, Medallion Architecture, Streaming & Batch Processing