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Job Summary
Synechron is seeking an experienced Cloud Data Engineer to design, develop, and optimize scalable, cloud-native data platforms supporting enterprise analytics and data-driven decision-making. This role involves building robust data pipelines, supporting cloud migrations, implementing data security and governance, and collaborating with data science, analytics, and platform teams to deliver reliable, secure, and high-performance data solutions aligned with organizational objectives.
Software Requirements
Required:
Extensive experience with cloud data services including Snowflake, BigQuery, Azure Data Lake, or Amazon Redshift for scalable data storage and warehousing
Hands-on expertise in building data pipelines using Spark (PySpark), Python, and SQL for large-scale data processing and transformation
Deep knowledge of cloud platforms (AWS, Azure, GCP) supporting data lakes, analytics, and ETL workflows
Proficiency with data modeling, query optimization, and security best practices
Experience supporting data migration, automation, and data governance using tools such as Terraform or CloudFormation
Preferred:
Knowledge of data lake architectures and metadata management frameworks
Experience with big data ecosystems like Hadoop, Kafka, or Hive supporting enterprise data needs
Exposure to machine learning workflows supporting data preparation and feature engineering
Overall Responsibilities
Design, develop, and support scalable data pipelines supporting enterprise analytics, reporting, and AI workflows
Implement data transformation, cleansing, and enrichment processes leveraging Spark, SQL, and Python for high data quality
Collaborate with data scientists, ML engineers, and platform teams to support data ingestion and feature processing
Support cloud migration initiatives, ensuring data platform scalability, security, and compliance
Automate data workflows, infrastructure provisioning, and deployment processes supporting CI/CD pipelines
Monitor data pipeline performance, troubleshoot issues, and optimize storage and compute resources
Enforce data security, privacy, and compliance policies across all platforms
Document architecture, data models, security policies, and operational procedures
Technical Skills (By Category)
Languages & Frameworks:
Python (advanced), SQL, Spark (PySpark), Scala (preferred) for large-scale data processing and automation
Data Management & Storage:
Snowflake, BigQuery, Azure Data Lake, Hadoop, data lakes, data warehouses, data modeling, query tuning
Cloud Platforms:
AWS, Azure, GCP supporting data lake, warehouse, and analytics deployment
Tools & Ecosystem:
Terraform, CloudFormation, Apache Airflow, Kubernetes, Docker, data pipeline orchestration tools
Analytics & Machine Learning:
Supporting data prep workflows for ML models using frameworks like TensorFlow or PyTorch (preferred)
Security & Governance:
Data encryption, access control, data masking, and compliance standards (GDPR, HIPAA, PCI DSS)
Experience Requirements
Minimum of 6 years supporting enterprise data platforms supporting analytics, BI, or ML workflows
Proven experience building, optimizing, and securing large-scale cloud data pipelines
Hands-on experience with cloud data storage platforms such as Snowflake and BigQuery
Experience supporting data migration projects and implementing data governance frameworks
Industry experience in finance, healthcare, or large enterprise data environments is a plus
Day-to-Day Activities
Design and implement scalable, secure data pipelines supporting analytics and ML workflows
Collaborate with data scientists, analytics, and platform teams to support data ingestion, feature engineering, and model deployment
Automate data workflows and infrastructure management supporting CI/CD pipelines
Troubleshoot pipeline performance, data quality issues, and security concerns
Support cloud migration projects by optimizing storage, compute, and data pipelines supporting multi-region deployments
Maintain documentation of data architecture, schemas, policies, and operational procedures
Monitor system health through dashboards, logs, and analytics tools to proactively address issues
Qualifications
Bachelor’s or Master’s degree in Data Science, Computer Science, or related discipline
6+ years supporting or developing enterprise data pipelines, warehouses, or lakes on cloud platforms
Certifications such as Google Professional Data Engineer, AWS Big Data certifications, or Azure Data Engineer are a plus
Demonstrated ability to deliver reliable, scalable, and compliant data solutions supporting enterprise analytics and ML
Professional Competencies
Analytical and troubleshooting skills for complex data pipeline issues
Effective communication skills for collaborating with technical teams and stakeholders
Leadership qualities to mentor junior engineers and foster best practices
Strategic thinking to design scalable, secure, and compliant data platforms supporting business growth
Adaptability to evolving technologies including cloud services, data governance, and analytics tools
Organizational skills to manage multiple projects and meet deadlines 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.
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