Job ID: H#13164 - Senior Data Migration Engineer
PLEASE NOTE: This is a 6 month renewable contract and needs to meet Client full-time conversion policies. Those dependent on a work permit sponsor now or anytime in the future (ie H1B, OPT, CPT, etc) do not meet Client requirements for this opening.
Position Summary: We are seeking a Senior Data Migration Engineer to support a strategic Oracle-to-Snowflake migration program. The role combines hands-on data engineering with business analysis responsibilities. The successful candidate will work with business stakeholders, data engineers, architects, and reporting teams to understand requirements, analyze existing Oracle-based solutions, identify gaps, and design scalable Snowflake-based solutions.
This position requires strong technical skills in database technologies, SQL, data engineering, and Python, along with the ability to gather requirements, perform impact assessments, and translate business needs into technical deliverables.
Role Focus:
- Data Engineering 40%
- Business Analysis / Requirements Gathering 30%
- Data Analysis and Validation 20%
- Automation, AI, and Continuous Improvement 10%
Key Responsibilities:
Data Migration and Engineering:
- Analyze Oracle databases, ETL processes, and reporting solutions to support migration planning.
- Design and implement Snowflake-based data solutions.
- Develop, optimize, and maintain complex SQL queries, views, and data transformation logic.
- Build and support ELT pipelines for loading and transforming data within Snowflake.
- Participate in data modeling, data integration, and performance optimization activities.
- Support testing, reconciliation, and validation of migrated data assets.
- Assist with data quality assessments and remediation efforts.
Requirements Gathering and Analysis:
- Partner with business and technology stakeholders to gather and document requirements.
- Perform current-state and future-state analysis.
- Conduct gap analyses between Oracle and Snowflake solutions.
- Identify migration risks, dependencies, and business impacts.
- Translate business requirements into technical designs and engineering tasks.
- Create functional and technical documentation.
Data Analysis and Validation:
- Analyze data to identify issues, anomalies, trends, and business impacts.
- Develop reconciliation processes to validate migration results.
- Investigate and resolve data discrepancies.
- Support user acceptance testing and business validation activities.
Automation and Continuous Improvement:
- Identify opportunities to automate manual processes and recurring workflows.
- Develop Python-based automation solutions where appropriate.
- Improve efficiency through reusable frameworks, scripts, and engineering best practices.
- Support implementation of monitoring, alerting, and operational controls.
AI and Modern Data Practices:
- Utilize AI-enabled tools to improve productivity, documentation, analysis, and development activities.
- Evaluate opportunities to leverage AI within data engineering and business processes.
- Promote AI literacy and responsible AI adoption across project teams
Required Qualifications:
- Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, or related discipline.
- 5+ years of experience in data engineering, data warehousing, data migration, or analytics engineering.
- Strong expertise in SQL development and query optimization.
- Strong understanding of relational database concepts and data modeling.
- Experience working with databases.
- Experience gathering business requirements and translating them into technical solutions.
- Demonstrated experience conducting gap analyses and impact assessments.
- Strong troubleshooting and problem-solving skills.
- Ability to communicate effectively with both technical and business audiences.
Preferred Qualifications:
- Experience with Snowflake architecture and implementation.
- Experience with Oracle-to-Snowflake migration initiatives.
- Strong Python programming skills.
- Experience developing ELT/ETL pipelines.
- Familiarity with data quality, metadata management, and data governance practices.
- Experience with workflow automation platforms and process orchestration tools.
- Exposure to cloud-based data platforms and modern data architectures.
- AI literacy and practical experience using AI tools to improve engineering and analytical workflows.
- Experience supporting Tableau, Power BI, or enterprise reporting environments.
Desired Characteristics:
- Strong systems thinker capable of understanding end-to-end data flows.
- Comfortable working between business and technical teams.
- Ability to independently drive ambiguous initiatives.
- Excellent analytical and critical thinking skills.
- Focus on data quality, scalability, and operational excellence.
- Strong documentation and communication skills.
- Continuous learning mindset with interest in emerging AI and automation technologies
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