Hiring: Senior Data Engineer Company: Incedo Inc. Location: Florham Park, NJ Job Posted Time: 2026-09-03 11:19:39 Target Skills & Keywords : AWS, Agile, CI/CD, Capital Markets, CloudFormation, CloudWatch, Data Lake, Data Pipeline, ELT, EMR, ETL, Encryption, Enterprise Architecture, GitHub, GitHub Actions, IAM, IaC, Iceberg, Infrastructure as Code, Jenkins, Kafka, Kinesis, Lambda, PostgreSQL, PySpark, Python, RBAC, Redshift, Regulatory Compliance, Root Cause Analysis, S3, SNS, SQL, Scrum, Snowflake, Spark, Step Functions, Terraform, Wealth Management About the job Experience: •12+ years of experience in Data Engineering •5+ years designing and implementing Required Skills: •We are seeking a highly skilled •To design, develop, and optimize large-scale data pipelines and ETL workflows on AWS. The ideal candidate will have strong expertise in AWS cloud-native data services, data modeling, and pipeline orchestration, with hands-on experience building robust and scalable data solutions for enterprise environments. •Design and implement incremental and CDC (Change Data Capture) data pipelines using AWS Glue, DMS, and Iceberg to support near real-time analytics. •Develop and maintain metadata-driven ETL frameworks to improve reusability, scalability, and operational efficiency across data platforms. •Create and manage partitioning, compaction, and optimization strategies for Iceberg datasets to reduce query latency and storage costs. •Build and orchestrate complex workflows using •AWS Step Functions, EventBridge, Lambda, and Glue Workflows for automated data processing. •Performance tuning and cost optimization of AWS Glue jobs by optimizing Spark configurations, worker types, partitioning, and job bookmarks. Qualifications: •, with at least 5+ years designing and implementing •AWS cloud-based data platforms and enterprise-scale data lakes •Strong hands-on expertise in AWS Glue, AWS DMS, Amazon S3, Amazon Redshift, Athena, Lambda, Step Functions, EventBridge, CloudWatch, SNS, and Glue Data Catalog •Advanced proficiency in PySpark, Spark, Python, and SQL •, with experience building reusable frameworks, ETL/ELT pipelines, and high-volume data transformation solutions. •Hands-on experience designing and implementing incremental and Change Data Capture (CDC) pipelines using AWS DMS, Glue, and related AWS services. •Strong experience with Apache Iceberg, including partitioning strategies, compaction, schema evolution, metadata management, performance optimization, and Iceberg catalog implementation. •Extensive experience building and supporting enterprise Data Lake architectures using Bronze, Silver, and Gold data layers with strong focus on scalability, reliability, governance, and self-service analytics. •AWS Step Functions, Glue Workflows, Lambda, and EventBridge •Strong knowledge of data modeling Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!