Snowflake Architect – ADF-to-Snowflake Migration, Data Modeling & ELTETL

Job Summary

Synechron is seeking a Snowflake Architect with 1013 years of overall data engineering or architecture experience including at least 45 years of hands-on Snowflake architecture and role will lead enterprise-scale data platform architecture modernization and migration initiatives with a specific focus on migrating pipelines and workloads from Azure Data Factory (ADF) to Snowflake. The successful candidate will re-engineer ADF-based ELT/ETL logic into Snowflake-native pipelines using Snowpipe Streams & Tasks dbt or comparable position contributes to business objectives by improving data platform scalability reliability governance performance cost efficiency and accessibility. The role also requires strong stakeholder management and the ability to translate business requirements into practical technical architecture.

Software Requirements

Required

• 1013 years of overall experience in data engineering data architecture or related roles.

• At least 45 years of hands-on Snowflake architecture and administration experience.

• Proven hands-on experience migrating pipelines and workloads from Azure Data Factory (ADF) to Snowflake.

• Experience re-engineering ADF-based ELT/ETL logic into Snowflake-native pipelines using:

  • Snowpipe

  • Streams & Tasks

  • dbt

  • Or comparable Snowflake-compatible approaches

• Strong command of Snowflake features including:

  • Snowpipe

  • Streams & Tasks

  • Time Travel

  • Zero-Copy Cloning

  • Secure Data Sharing

  • Virtual warehouse cost management

• Deep expertise in dimensional modeling data vault and enterprise data warehouse design principles.

• Strong SQL skills for data transformation analysis optimization and troubleshooting.

• Hands-on experience with at least one ELT/ETL tool including Informatica dbt Matillion Talend or ADF.

• Working knowledge of at least one cloud platform: AWS Azure or GCP.

• Understanding of cloud-native data services and data platform integration patterns.

• Experience with Python or another scripting language for automation and pipeline orchestration.

• Experience leading data platform migrations at enterprise scale.

• Ability to translate business requirements into technical architecture data models migration plans and implementation guidance.

Preferred

• Experience in manufacturing engineering or BFSI environments.

• Experience designing enterprise-scale Snowflake migration strategies landing zones operating models and governance frameworks.

• Familiarity with data quality data lineage metadata management data cataloging and data observability.

• Experience with real-time near-real-time and batch data-processing architectures.

• Exposure to cloud-native orchestration serverless data services event-driven pipelines and automated deployment.

• Familiarity with Infrastructure as Code and CI/CD practices for data platforms.

• Experience optimizing Snowflake warehouses workload management storage query performance and consumption costs.

• Relevant Snowflake cloud data architecture data engineering or enterprise architecture certifications.

Overall Responsibilities

• Define Snowflake architecture strategies target-state designs reference architectures technical standards and implementation roadmaps.

• Lead the migration of pipelines and workloads from Azure Data Factory to Snowflake.

• Analyze existing ADF-based ELT/ETL processes and re-engineer them into Snowflake-native pipelines using Snowpipe Streams & Tasks dbt or suitable alternatives.

• Design scalable secure reliable and cost-efficient Snowflake data platforms.

• Apply Snowflake capabilities such as Time Travel Zero-Copy Cloning Secure Data Sharing Snowpipe Streams & Tasks and warehouse cost management.

• Design and govern dimensional models data vault structures enterprise data warehouses data marts and related data platforms.

• Develop and review complex SQL for transformation validation data quality reconciliation and performance optimization.

• Design and implement batch incremental streaming and event-driven data-processing patterns where required.

• Establish data platform standards for ingestion transformation storage consumption security monitoring recovery and operational support.

• Use Python or another scripting language to automate pipeline orchestration validation monitoring deployment and operational processes.

• Collaborate with data engineers application teams cloud teams security teams business stakeholders and delivery teams.

• Translate business requirements into data architecture logical and physical data models migration designs and technical delivery plans.

• Lead technical discussions design reviews architecture decisions code reviews and migration planning sessions.

• Identify migration dependencies technical risks data-quality issues performance constraints and operational impacts.

• Support testing validation reconciliation cutover rollback planning production stabilization and post-migration optimization.

• Manage Snowflake compute and storage usage to improve performance while supporting responsible and sustainable resource consumption.

• Provide technical leadership for enterprise-scale data platform migration initiatives and ensure delivery against agreed quality timeline security and cost objectives.

Strategic Objectives

• Modernize ADF-based data pipelines and workloads through Snowflake-native architecture.

• Establish scalable and governed data platforms that support analytics reporting integration and business decision-making.

• Improve data quality reliability lineage accessibility and processing efficiency.

• Reduce unnecessary platform complexity and improve operational support through standardization and automation.

• Optimize Snowflake resource consumption warehouse utilization query performance and overall platform cost.

Performance Outcomes

• ADF pipelines and workloads are migrated to Snowflake with validated functionality data integrity and agreed business continuity controls.

• Snowflake-native pipelines meet defined requirements for scalability reliability performance security and maintainability.

• Data models and warehouse designs support consistent accurate and reusable data consumption.

• Snowflake compute and storage resources are monitored and managed according to workload needs and cost objectives.

• Technical architecture migration plans data models decisions risks and operational procedures are clearly documented.

• Enterprise stakeholders receive practical architecture recommendations aligned with business requirements and delivery constraints.

Technical Skills (By Category)

Programming Languages and Scripting

Essential

• Strong SQL skills for data transformation querying validation reconciliation troubleshooting and optimization.

• Experience with Python or another scripting language for automation and pipeline orchestration.

• Ability to write scripts for data validation pipeline control monitoring deployment and operational support.

• Ability to interpret and re-engineer transformation logic from existing ELT/ETL workflows.

Preferred

• Experience developing reusable Python libraries or automation frameworks for data platforms.

• Familiarity with scripting standards testing version control error handling logging and secure configuration.

Databases/Data Management

Essential

• Hands-on Snowflake architecture and administration experience of at least 45 years.

• Strong understanding of dimensional modeling data vault and enterprise data warehouse design principles.

• Experience designing fact tables dimensions relationships keys historization data marts and analytical structures.

• Experience with Snowflake Snowpipe Streams & Tasks Time Travel Zero-Copy Cloning Secure Data Sharing and warehouse cost management.

• Experience migrating ADF-based ELT/ETL logic into Snowflake-native pipelines.

• Understanding of data ingestion transformation incremental processing data quality reconciliation lineage and lifecycle management.

• Ability to design data platforms for batch real-time and near-real-time processing.

Preferred

• Experience with data lakes lakehouses data marts semantic layers and enterprise reporting platforms.

• Familiarity with data governance metadata management data cataloging data classification and data observability.

• Experience with data retention archiving recovery and storage optimization.

Cloud Technologies

Essential

• Working knowledge of at least one cloud platform: AWS Azure or GCP.

• Understanding of cloud-native data services and their integration with Snowflake.

• Experience designing secure and scalable cloud-based data architectures.

• Understanding of cloud networking identity and access management storage monitoring availability and resource management.

Preferred

• Experience integrating Snowflake with cloud storage messaging orchestration monitoring and serverless services.

• Familiarity with hybrid and multi-cloud data architectures.

• Experience optimizing cloud data services for performance cost and sustainable resource consumption.

Frameworks and Libraries

Essential

• Hands-on experience with at least one ELT/ETL tool including Informatica dbt Matillion Talend or ADF.

• Experience designing and implementing Snowflake-native ingestion and transformation frameworks.

• Understanding of pipeline orchestration dependency management error handling retry logic data validation and operational recovery.

• Experience applying reusable patterns for ingestion transformation incremental loading and data reconciliation.

Preferred

• Experience with dbt models tests documentation macros and deployment practices.

• Familiarity with event-driven and streaming data frameworks.

• Exposure to data-quality observability lineage and pipeline-monitoring frameworks.

Development Tools and Methodologies

Essential

• Experience leading enterprise-scale data platform migration initiatives.

• Experience with architecture documentation technical design reviews migration planning and implementation governance.

• Understanding of software development lifecycle practices for data platforms.

• Ability to define technical standards reference patterns operational procedures and support models.

• Experience with testing data reconciliation performance testing cutover planning rollback planning and production stabilization.

• Ability to collaborate with business data cloud security application and infrastructure teams.

Preferred

• Experience with Git CI/CD pipelines Infrastructure as Code and automated data-platform deployment.

• Familiarity with Agile iterative or structured delivery methodologies.

• Experience with automated data-quality checks deployment validation and platform compliance controls.

• Exposure to architecture review processes and enterprise data governance forums.

Security Protocols

Essential

• Understanding of Snowflake security including role-based access control least-privilege access secure data sharing authentication and authorization.

• Experience defining access controls for databases schemas tables views warehouses pipelines and data-sharing capabilities.

• Awareness of data protection encryption masking privacy auditability retention and compliance requirements.

• Ability to ensure data migration and platform operations follow approved security governance and change-management controls.

Preferred

• Experience with dynamic data masking row-level access policies network controls key management and sensitive-data handling.

• Familiarity with cloud security controls and secure integration between Snowflake and cloud-native services.

• Experience supporting regulated or controlled data environments including BFSI data platforms.

Experience Requirements

• 1013 years of overall data engineering or architecture experience.

• At least 45 years of hands-on Snowflake architecture and administration experience.

• Proven hands-on experience migrating pipelines and workloads from Azure Data Factory to Snowflake.

• Demonstrable experience re-engineering ADF-based ELT/ETL logic into Snowflake-native pipelines using Snowpipe Streams & Tasks dbt or equivalent approaches.

• Strong experience with Snowflake architecture administration performance management security data sharing and cost optimization.

• Deep experience with dimensional modeling data vault and enterprise data warehouse design.

• Strong SQL skills and hands-on experience with at least one ELT/ETL tool including Informatica dbt Matillion Talend or ADF.

• Working knowledge of AWS Azure or GCP and cloud-native data services.

• Experience using Python or another scripting language for automation and pipeline orchestration.

• Prior experience leading data platform migrations at enterprise scale.

• Experience in manufacturing engineering or BFSI environments is preferred.

• Candidates may qualify through equivalent hands-on data architecture and migration experience if they can demonstrate comparable Snowflake delivery ADF migration enterprise data modeling platform governance and stakeholder outcomes.

Day-to-Day Activities

• Review current ADF pipelines workloads dependencies data models transformation logic and operational issues then define Snowflake-native migration and modernization approaches.

• Collaborate with data engineers cloud teams application teams security teams business stakeholders and delivery teams through design reviews planning sessions technical workshops and migration checkpoints.

• Produce target-state architectures data models migration plans Snowflake pipeline designs SQL transformations cost assessments validation results technical decisions and operational documentation.

• Make architecture decisions within the assigned scope resolve technical dependencies guide implementation teams manage migration risks and escalate decisions requiring broader governance or stakeholder approval.

Qualifications

• Bachelors degree in Computer Science Information Technology Engineering Data Engineering or a related field; equivalent relevant professional experience may also be considered.

• 1013 years of overall data engineering or architecture experience including at least 45 years of hands-on Snowflake architecture and administration.

• Relevant Snowflake cloud data architecture data engineering or enterprise architecture certifications are preferred.

• Training in Snowflake architecture ADF migration data vault dimensional modeling ELT/ETL cloud-native data services SQL Python security and cost management is beneficial.

• Maintain continuous professional development in Snowflake capabilities data architecture cloud platforms migration methods data governance automation security performance and sustainable data-platform operations.

Professional Competencies

• Apply structured analysis and problem-solving to assess migration complexity pipeline dependencies data quality performance security and operational risks.

• Provide technical leadership across data engineering architecture cloud security application and delivery teams while supporting shared implementation outcomes.

• Translate business requirements into clear technical architecture data models migration plans platform standards and implementation guidance.

• Adapt architecture and migration approaches as business priorities data requirements technology capabilities and delivery constraints change.

• Identify opportunities to improve data-platform scalability automation reuse reliability performance cost efficiency and sustainable resource utilization.

• Prioritize architecture decisions migration activities technical risks stakeholder needs and delivery commitments while maintaining clear documentation and follow-through.

SYNECHRONS DIVERSITY & INCLUSION STATEMENT

Diversity & Inclusion are fundamental to our culture and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity Equity and Inclusion (DEI) initiative Same Difference is committed to fostering an inclusive culture promoting equality diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger successful businesses as a global company. We encourage applicants from across diverse backgrounds race ethnicities religion age marital status gender sexual orientations or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements mentoring internal mobility learning and development programs and more.

All employment decisions at Synechron are based on business needs job requirements and individual qualifications without regard to the applicants gender gender identity sexual orientation race ethnicity disabled or veteran status or any other characteristic protected by law.

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