Job Summary
Synechron is seeking a highly skilled Cloud Data Engineer to design, develop, and maintain scalable, high-quality data pipelines across cloud platforms (AWS, Azure, or GCP). This role involves working with structured and unstructured data, optimizing ETL/ELT processes, and supporting business analytics and data-driven decision-making. The successful candidate will collaborate with analytics and engineering teams to ensure data integrity, security, and performance, contributing to the organization's strategic initiatives in digital transformation and operational excellence.
Software Requirements
- Required:
- Proficiency in cloud platforms including AWS, Azure, or GCP with experience supporting enterprise data environments
- Strong knowledge of SQL, Python, and Spark for data processing and pipeline development
- Hands-on experience with cloud data services such as Amazon Redshift, Google BigQuery, Snowflake, or Azure Synapse
- Experience with ETL/ELT processes for both structured and unstructured data
- Familiarity with data orchestration tools like Apache Airflow or similar
- Understanding of data security, privacy, and compliance best practices
- Preferred:
- Experience with cloud infrastructure automation tools such as Terraform or CloudFormation
- Knowledge of data governance and metadata management solutions
- Exposure to visualization and BI tools integrated with data pipelines
Overall Responsibilities
- Design, build, and optimize scalable data pipelines in cloud environments supporting enterprise analytics and operations
- Develop and enhance ETL/ELT workflows for diverse data sources, ensuring data quality and accuracy
- Collaborate with analytics, data science, and engineering teams to enable data ingestion, processing, and visualization
- Monitor data pipeline performance and troubleshoot bottlenecks, implementing improvements proactively
- Ensure data security, access controls, and regulatory compliance in line with organizational policies
- Support cloud migration initiatives, evaluating new data technologies and supporting proof-of-concept deployments
- Document system architecture, pipeline workflows, and operational procedures for ongoing maintenance and audits
Technical Skills (By Category)
- Programming Languages: Required: Python, SQL Preferred: Spark (PySpark), Scala, Java for data processing and automation scripting
- Databases & Data Management: Relational databases (PostgreSQL, MySQL, SQL Server), cloud data warehouses (Redshift, BigQuery, Snowflake, Synapse), data lake architecture
- Cloud Technologies: AWS, Azure, or GCP supporting cloud-native data storage, processing, and deployment
- Frameworks & Libraries: Spark (PySpark/Scala), Hadoop ecosystem tools, data integration libraries (e.g., Apache NiFi)
- Tools & Orchestration: Airflow, Terraform, CloudFormation, Jenkins, Git, Docker, Kubernetes
- Security & Compliance: Data masking, encryption, identity and access management, compliance with GDPR, HIPAA, or industry-specific standards
Experience Requirements
- Minimum of 5 years supporting large-scale data pipelines in cloud environments
- Proven experience with ETL/ELT processes supporting enterprise analytics
- Hands-on experience with cloud-based data warehouses and data lake architectures
- Demonstrated success optimizing data workflows for performance and reliability
- Experience supporting cloud migrations, automation, and infrastructure as code is advantageous
- Industry experience in finance, healthcare, retail, or enterprise IT preferred but not mandatory
Day-to-Day Activities
- Design, implement, and support scalable data pipelines for structured and unstructured data sources
- Collaborate with data scientists, analysts, and software engineers to develop efficient data workflows
- Automate data ingestion, transformation, and pipeline deployment processes, supporting CI/CD practices
- Troubleshoot pipeline failures, optimize query performance, and implement data security controls
- Support cloud migration activities, including validating data integrity and performance benchmarks
- Maintain operational documentation, data governance policies, and system architecture diagrams
- Monitor system health and data quality metrics to ensure continuous reliability
Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Information Technology, or related field
- Minimum of 5 years of experience designing and managing enterprise-level data pipelines and warehouses supported by cloud platforms
- Certifications such as AWS Certified Data Analytics, Google GCP Data Engineer, or Azure Data Engineer certifications preferred
- Experience implementing cloud-native data solutions in regulated or enterprise environments
Professional Competencies
- Strong analytical skills to troubleshoot data pipeline issues and optimize performance
- Excellent communication skills for collaborating across technical teams and business stakeholders
- Leadership qualities to guide junior team members and promote best practices in data engineering
- Strategic mindset to implement secure, scalable, and compliant data architectures
- Curiosity and adaptability to stay current with emerging data technologies and industry standards
- Time management skills to deliver high-quality data solutions within deadlines
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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