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Job Summary
Synechron is seeking an experienced Cloud Data Engineer to design, develop, and support scalable, cloud-native data platforms supporting enterprise analytics and data modernization initiatives. The role involves building robust ELT pipelines, optimizing data models, and implementing data governance standards across cloud environments such as AWS, GCP, or Azure. The successful candidate will collaborate with analytics, data science, and platform teams to enable impactful data-driven insights, supporting operations, strategic planning, and innovation.
Software Requirements
Required:
In-depth experience with Snowflake data platform for scalable data warehousing solutions
Hands-on expertise in DBT for data transformations, testing, and documentation
Strong knowledge of AWS cloud services such as S3, IAM, Glue, and supporting data workflows (GCP or Azure experience preferred)
Practical experience with orchestration tools such as Apache Airflow for pipeline management
Advanced SQL skills for data modeling, query tuning, and performance optimization
Python proficiency for scripting, automation, and data processing tasks
Knowledge of big data ecosystem tools such as Spark, Hadoop, or NiFi (preferred)
Preferred:
Experience with Infrastructure as Code tools such as Terraform or CloudFormation
Familiarity with BI tools like Power BI or Tableau for reporting integrations
Exposure to data governance, security standards, and compliance frameworks (GDPR, HIPAA, etc.)
Overall Responsibilities
Design, build, and optimize scalable data pipelines within cloud environments supporting enterprise analytics and reporting
Develop data transformation workflows using DBT, ensuring accuracy, quality, and documentation
Collaborate with data scientists, analytics teams, and platform engineers to support data ingestion, feature engineering, and ML workflows
Monitor pipeline performance, troubleshoot issues, and implement enhancements for efficiency and resilience
Support cloud migration, supporting multi-region, hybrid architectures for data platforms
Enforce data security, privacy, and governance policies across pipelines and data stores
Automate data workflows and infrastructure deployment supporting CI/CD pipelines
Document system architecture, data schemas, transformation logic, and operational procedures
Technical Skills (By Category)
Languages & Scripts:
Required: Python, SQL (PostgreSQL, MySQL, or equivalent), Bash for automation
Preferred: Scala, R, or Java for supporting big data integrations
Data Management & Storage:
Snowflake, data models, query optimization, data security best practices, data governance practices
Cloud Platforms:
AWS (S3, Glue, Redshift), GCP (BigQuery, Dataflow), Azure support supporting migration and scaling
Frameworks & Ecosystems:
DBT, Spark (PySpark), Hadoop, NiFi (preferred)
Orchestration & Automation:
Apache Airflow, Terraform, CloudFormation, Jenkins, Git, CI/CD pipelines support for data deployment
Security & Compliance:
Data encryption, access control, GDPR/HIPAA compliance standards, audit logging
Experience Requirements
5+ years supporting or developing large-scale, enterprise data pipelines in cloud environments
Proven success in optimizing data workflows, data modeling, and pipeline automation
Hands-on experience with cloud data platforms like Snowflake and supporting data ecosystems (Spark, Hadoop, NiFi)
Experience supporting data governance, security, and compliance initiatives (GDPR, HIPAA, etc.)
Strong background supporting data science, analytics, or ML workflows preferred
Day-to-Day Activities
Develop, tune, and support scalable data pipelines for enterprise analytics and reporting
Collaborate with cross-functional teams to gather data requirements and translate them into technical solutions
Automate data ingestion, transformation, and deployment workflows supporting CI/CD practices
Troubleshoot data pipeline issues, perform performance tuning, and implement security controls
Support cloud migration efforts, data governance initiatives, and pipeline automation projects
Document architecture, schemas, and operational procedures
Monitor system health, data quality, and compliance status to ensure operational stability and security standards
Qualifications
Bachelor’s or Master’s degree in Data Science, Computer Science, or related disciplines
5+ years of experience supporting enterprise data platforms in cloud environments
Certifications such as GCP Professional Data Engineer, AWS Data Analytics or equivalent are advantageous
Proven experience in building, managing, and optimizing large-scale data pipelines supporting analytics and ML workflows
Professional Competencies
Analytical problem-solving skillset, particularly for optimizing data workflows at scale
Effective communication with technical teams and business stakeholders for data requirements and governance
Mentoring abilities to guide junior data engineers and promote best practices
Strategic thinking for designing scalable, secure cloud data ecosystems supporting enterprise needs
Adaptability and continuous learning to leverage new data technologies and compliance standards
Organization and time management skills for handling multiple data projects efficiently
SYNECHRON’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.
Candidate Application Notice
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