Cloud Data Engineer - Snowflake, DBT, Airflow and AWS.

Job Summary
Synechron is seeking a highly skilled Cloud Data Engineer to design, develop, and optimize scalable, cloud-based data pipelines supporting advanced analytics and data warehousing initiatives. In this role, you will leverage AWS cloud services, orchestrate data workflows with Airflow, build modular data transformation models using DBT, and manage Snowflake data warehouses. Your expertise will enable reliable, high-performance data architectures aligned with enterprise objectives, facilitating data-driven decision-making and operational efficiency across large-scale systems.

Software Requirements

• Required: AWS services (S3, Lambda, Glue, EC2), Apache Airflow, DBT, Snowflake, SQL (MySQL, PostgreSQL, or Snowflake), Git, Jenkins, CI/CD automation tools (GitHub Actions, GitLab CI, Azure DevOps)

• Preferred: Kubernetes, Terraform, DataOps tools, monitoring/alerting platforms (CloudWatch, Prometheus, Grafana, Splunk)

• Experience level: 5+ years supporting enterprise cloud data pipelines, migration, and automation in large organizations

Overall Responsibilities

• Design and implement scalable data pipelines utilizing AWS cloud services for analytics, reporting, and data management

• Develop and maintain workflows with Apache Airflow to automate data ingestion, transformation, and loading processes

• Build modular, testable data transformation logic using DBT, ensuring data quality and consistency across systems

• Manage and optimize Snowflake data warehouses for high-throughput analytical workloads

• Collaborate with cross-disciplinary teams to gather requirements, validate data models, and implement solutions

• Monitor pipeline health, troubleshoot issues, and optimize performance and reliability

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

• Support migration projects, data integration, and cloud transitioning efforts supporting enterprise architecture

• Document architecture, data flow, and operational procedures for ongoing support and compliance

Technical Skills (By Category)

• Programming Languages:

  • Essential: SQL, Python, Shell scripting

  • Preferred: Java, Scala (for big data processing)

• Data Management & Databases:

  • Snowflake, PostgreSQL, MySQL; schema design, data validation, and performance tuning

• Cloud Technologies:

  • AWS (preferred), Azure (preferred), basic support for GCP supported

• Frameworks & Libraries:

  • DBT, Apache Airflow, Spark, Presto, Kafka (preferred for streaming)

• Development Tools & Methodologies:

  • Terraform, CloudFormation, Git, Jenkins, CI/CD pipelines, Agile/Scrum, DataOps best practices

• Security & Compliance:

  • Data encryption, IAM policies, audit logging, compliance with data standards (GDPR, HIPAA)

Experience Requirements

• 5+ years supporting enterprise big data or cloud data infrastructure

• Proven experience designing and operating scalable data pipelines on cloud platforms

• Hands-on expertise with AWS, Snowflake, Airflow, and DBT for ETL and data management

• Experience supporting data migration, automation, and performance tuning in large systems

• Industry experience in finance, healthcare, retail, or enterprise analytics is preferred; relevant large-scale data support experience in other sectors also acceptable

Day-to-Day Activities

• Develop, support, and optimize cloud data pipelines for enterprise analytics platforms

• Automate data workflows, deployment pipelines, and infrastructure provisioning

• Troubleshoot pipeline failures, data quality issues, and operational bottlenecks

• Collaborate with data scientists, analysts, and enterprise teams on data ingestion, transformation, and integration projects

• Support migration, cloud adoption, and system upgrades in line with enterprise architecture strategies

• Monitor and tune system performance, capacity, and security standards

• Maintain documentation for architecture, data models, and operational procedures

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, or related fields

• 6+ years in enterprise cloud data environment support, automation, and pipeline management

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

• Strong coding, troubleshooting, and optimization skills

• Excellent collaboration, communication, and stakeholder engagement skills

• Experience working within large-scale data ecosystems supporting business analytics

Professional Competencies

• Critical thinking and analytical problem-solving for high-volume data pipelines

• Leadership and team collaboration in cross-functional environments

• Effective communication for stakeholder alignment and documentation

• Adaptability to evolving cloud and data technologies

• Ownership of system reliability, security, and operational excellence

• Time management and planning skills to meet continuous delivery goals

S​YNECHRON’S 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 applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

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