Enterprise Data Engineer - Cloud Platforms, Big Data, Data Governance & Automation Support

Requirements

• Bachelor's or Master's degree in Data Science,

Benefits

Additional Information

Job Summary Synechron is seeking an experienced Data Engineer supported by advanced cloud, blockchain, IoT, or mobile technologies to develop scalable data solutions supporting enterprise applications and analytics. This role involves designing, implementing, and optimizing data pipelines, collaborating with cross-functional teams to address diverse data needs, and supporting continuous system improvements. The candidate will leverage their expertise in programming, databases, and emerging tech to enable data-driven decision-making and operational excellence. Software Requirements Required Software Proficiency: Programming: Java, Python, or Node.js - extensive hands-on experience supporting data pipelines, automation, or system integrations (latest versions preferred) Databases: SQL (MySQL, Oracle, PostgreSQL, SQL Server) - deep experience in data modeling, querying, and optimization supporting enterprise data management Cloud Platforms: AWS, Azure, or GCP - proven support for cloud-native data architecture and deployment (supporting 4+ years) Data Frameworks & Libraries: Pandas, NumPy, Spark, or similar supporting large-scale data processing and analytics workflows Data Operations & ETL/ELT tools supporting automation and data transformation support Preferred Software Skills: Cloud-native services: AWS Glue, Data Factory, Azure Data Lake support supporting data ingestion and migration support Advanced data processing: Hadoop, Kafka, or similar for streaming data and event-driven architectures support Automation: Terraform, Ansible, support for infrastructure as code and environment automation support Overall Responsibilities Design, develop, and maintain scalable data pipelines supporting enterprise analytics, migration, and operational reporting needs Build and optimize cloud-native data architectures, ensuring reliability, scalability, and security align with industry standards Collaborate with data architects, data scientists, and business stakeholders to gather requirements and deliver effective data solutions Support data ingestion, transformation, validation, and reconciliation activities supporting data integrity and compliance Drive automation initiatives to streamline data workflows, environment provisioning, and deployment processes Monitor system performance, troubleshoot issues, and implement performance, security, and operational improvements Support cloud migration, environment setup, and data platform upgrades supporting enterprise resilience Maintain detailed documentation of data architecture, workflows, security policies, and operational procedures Technical Skills (By Category) Languages & Data Processing (Essential): Java, Python, or Node.js supporting data pipeline development and automation Spark, Hadoop, or similar frameworks supporting big data processing and streaming data Databases & Data Management: SQL-based systems: MySQL, Oracle, PostgreSQL, SQL Server supporting data validation and query optimization NoSQL: Kafka, DynamoDB, or similar supporting streaming data and real-time processing (preferred) Cloud & Infrastructure: AWS, Azure, or GCP supporting deployment, scaling, and cloud-native data architecture (preferred) Automation & Infrastructure as Code: Terraform, Ansible supporting environment provisioning and automation support Monitoring & Security: CloudWatch, Prometheus, DataDog supporting system health monitoring and security support Experience Requirements 5+ years supporting large-scale, scalable data pipelines, cloud-native applications, and enterprise data platforms Proven expertise designing, deploying, and managing data workflows supporting analytics, migration, and real-time processing Extensive experience supporting cloud migration initiatives and automation of data processes supporting operational resilience Knowledge supporting compliance and security in regulated environments (preferred) Demonstrated ability to troubleshoot, optimize, and support high-volume, secure data systems supporting enterprise decision-making Day-to-Day Activities Develop, test, and maintain scalable ETL/ELT pipelines supporting enterprise analytics, migration, and operational workflows Collaborate with data scientists, data architects, and business teams to implement data pipelines supporting business needs Support cloud migration, data platform upgrades, and automation support activities for operational resilience Monitor data pipeline performance, troubleshoot failures, and optimize for efficiency and scalability Conduct root cause analysis, implement performance tuning, and validate data integrity support supporting compliance standards Automate infrastructure provisioning, environment setup, and data flow management supporting DevOps practices supporting agile delivery Document data architecture, operational procedures, and security policies supporting operational audit and compliance

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