Cloud Data Engineer | AWS, Snowflake, Airflow, Data Pipelines, Infrastructure Automation

Job Summary
Synechron is seeking an experienced Cloud Data Engineer to develop and optimize cloud-based data pipelines supporting enterprise this role you will leverage AWS services orchestrate workflows with Airflow execute data transformations with DBT and manage Snowflake data warehouses. Your expertise will enable efficient and reliable data operations supporting strategic decision-making and data-driven initiatives. You will collaborate with cross-functional teams to deliver scalable high-quality data solutions aligned with organizational goals.

Software Requirements

• Required: AWS (S3 Lambda Glue EC2 IAM) Apache Airflow DBT Snowflake SQL (MySQL PostgreSQL or Snowflake) Git CI/CD tools (Jenkins GitLab CI)

• Preferred: AWS CloudFormation/Terraform AWS Glue Kubernetes Prometheus Grafana DataOps tools Python scripting

• Experience level: 5 years supporting enterprise data pipelines cloud infrastructure and automation in a large-scale environment

Overall Responsibilities

• Design build and manage scalable data pipelines on AWS for analytics and reporting purposes

• Develop and maintain workflows using Apache Airflow to orchestrate data ingestion processing and transformation tasks

• Construct modular testable data models and transformations using DBT ensuring data quality and correctness

• Manage and optimize Snowflake data warehouses to support high-performance analytics workloads

• Collaborate across teams to gather requirements validate data processes and implement scalable solutions

• Monitor data pipeline health troubleshoot issues and optimize for performance and reliability

• Automate deployment testing and operational workflows to support continuous integration and delivery

• Document architecture workflows and operational procedures for transparency and compliance

• Conduct data validation performance tuning and capacity planning activities

Technical Skills (By Category)

• Programming Languages:

  • Essential: SQL Python (preferred) shell scripting for automation

  • Preferred: Java JavaScript or other scripting languages for data workflow automation

• Data Management & Databases:

  • Snowflake PostgreSQL MySQL and experience with data modeling query optimization and data validation

• Cloud Technologies:

  • AWS (S3 Lambda Glue EC2 IAM) cloud deployment security models and multi-cloud concepts (preferred)

• Frameworks & Libraries:

  • DBT Apache Airflow Prometheus Grafana data orchestration SDKs security libraries (OAuth2 SAML)

• Development & Automation Tools:

  • Git Jenkins Terraform CloudFormation CI/CD pipelines containerization (Docker Kubernetes)

• Security & Compliance:

  • Data encryption IAM roles access controls compliance standards (GDPR HIPAA SOC)

Experience Requirements

• 5 years supporting cloud data pipelines data warehouse management and automation in large environments

• Proven experience designing building and operating scalable high-availability data workflows in AWS

• Expertise in Snowflake data warehousing and data transformation using DBT

• Strong troubleshooting and performance tuning skills with a focus on data throughput and reliability

• Industry experience in finance banking fintech or enterprise analytics is preferred; equivalent large-scale data support experience in other sectors acceptable

Day-to-Day Activities

• Develop and optimize cloud data pipelines supporting enterprise dashboards and analytics

• Collaborate with data scientists analysts and engineering teams to define and implement data workflows

• Monitor system health using Prometheus Grafana and cloud-native tools; troubleshoot operational issues

• Automate deployment configuration and scaling activities with Infrastructure as Code (Terraform CloudFormation)

• Conduct root cause analysis and performance tuning for data pipelines and warehouse systems

• Maintain operational documentation runbooks and process standards

• Support cloud migration system upgrades and security compliance tasks

• Implement automation to reduce manual intervention and improve reliability

Qualifications

• Bachelors or Masters degree in Computer Science Data Engineering or related field

• 5 years supporting enterprise-level cloud data infrastructure and pipelines

• Certifications such as AWS Data Analytics Specialty AWS Solutions Architect or equivalent are advantageous

• Hands-on experience with AWS Snowflake Airflow DBT and SQL optimization

• Proven record of supporting data platforms in regulated or high-availability environments

• Strong troubleshooting analytical and communication skills

• Ability to work independently and coordinate with cross-functional teams

Professional Competencies

• Analytical mindset with a focus on data quality performance and operational stability

• Leadership and teamwork capabilities for cross-team collaboration and mentoring

• Effective communication to translate technical outcomes for diverse audiences

• Adaptability and continuous learning to stay current with emerging data technologies

• Ownership of data reliability security and process automation

• Excellent time management and prioritization skills to meet project deliverables